5,926 results on '"James, Richard"'
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2. Protective effect of Phaleria macrocarpa methanolic fruit extract against oxidative stress in brine shrimps
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Hazalin, Nurul Aqmar Mohamad Nor, Halim, Hasseri, Rosli, Izzah Firzana, Nazri, Nur Aqilah, Mohsin, Hannis Fadzillah, Zohdi, Rozaini Mohd, Ariestanti, Donna Maretta, and James, Richard Johari
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- 2024
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3. Asymptotically Stable Data-Driven Koopman Operator Approximation with Inputs using Total Extended DMD
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Lortie, Louis and Forbes, James Richard
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Electrical Engineering and Systems Science - Systems and Control - Abstract
The Koopman operator framework can be used to identify a data-driven model of a nonlinear system. Unfortunately, when the data is corrupted by noise, the identified model can be biased. Additionally, depending on the choice of lifting functions, the identified model can be unstable, even when the underlying system is asymptotically stable. This paper presents an approach to reduce the bias in an approximate Koopman model, and simultaneously ensure asymptotic stability, when using noisy data. Additionally, the proposed data-driven modeling approach is applicable to systems with inputs, such as a known forcing function or a control input. Specifically, bias is reduced by using a total least-squares, modified to accommodate inputs in addition to lifted inputs. To enforce asymptotic stability of the approximate Koopman model, linear matrix inequality constraints are augmented to the identification problem. The performance of the proposed method is then compared to the well-known extended dynamic mode decomposition method and to the newly introduced forward-backward extended dynamic mode decomposition method using a simulated Duffing oscillator dataset and experimental soft robot arm dataset., Comment: 18 pages, 6 figures
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- 2024
4. Passivity-Based Gain-Scheduled Control with Scheduling Matrices
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Moalemi, Sepehr and Forbes, James Richard
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Electrical Engineering and Systems Science - Systems and Control - Abstract
This paper considers gain-scheduling of very strictly passive (VSP) subcontrollers using scheduling matrices. The use of scheduling matrices, over scalar scheduling signals, realizes greater design freedom, which in turn can improve closed-loop performance. The form and properties of the scheduling matrices such that the overall gain-scheduled controller is VSP are explicitly discussed. The proposed gain-scheduled VSP controller is used to control a rigid two-link robot subject to model uncertainty where robust input-output stability is assured via the passivity theorem. Numerical simulation results highlight the greater design freedom, resulting in improved performance, when scheduling matrices are used over scalar scheduled signals., Comment: To be published in IEEE Conference on Control Technology and Applications (CCTA) 2024
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- 2024
5. The Harmonic Exponential Filter for Nonparametric Estimation on Motion Groups
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Saavedra-Ruiz, Miguel, Parkison, Steven A., Arora, Ria, Forbes, James Richard, and Paull, Liam
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Computer Science - Robotics - Abstract
Bayesian estimation is a vital tool in robotics as it allows systems to update the belief of the robot state using incomplete information from noisy sensors. To render the state estimation problem tractable, many systems assume that the motion and measurement noise, as well as the state distribution, are all unimodal and Gaussian. However, there are numerous scenarios and systems that do not comply with these assumptions. Existing non-parametric filters that are used to model multimodal distributions have drawbacks that limit their ability to represent a diverse set of distributions. In this paper, we introduce a novel approach to nonparametric Bayesian filtering to cope with multimodal distributions using harmonic exponential distributions. This approach leverages two key insights of harmonic exponential distributions: a) the product of two distributions can be expressed as the element-wise addition of their log-likelihood Fourier coefficients, and b) the convolution of two distributions can be efficiently computed as the tensor product of their Fourier coefficients. These observations enable the development of an efficient and exact solution to the Bayes filter up to the band limit of a Fourier transform. We demonstrate our filter's superior performance compared with established nonparametric filtering methods across a range of simulated and real-world localization tasks., Comment: Preprint under review. Code available at https://github.com/montrealrobotics/harmonic-filter. Webpage and additional videos at https://montrealrobotics.ca/hef/
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- 2024
6. Speed and shape of population fronts with density-dependent diffusion
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Stokes, Beth M., Rogers, Tim, and James, Richard
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Quantitative Biology - Populations and Evolution ,Mathematics - Dynamical Systems - Abstract
We investigate travelling wave solutions in reaction-diffusion models of animal range expansion in the case that population diffusion is density-dependent. We find that the speed of the selected wave depends critically on the strength of diffusion at low density. For sufficiently large low-density diffusion, the wave propagates at a speed predicted by a simple linear analysis. For small or zero low-density diffusion, the linear analysis is not sufficient, but a variational approach yields exact or approximate expressions for the speed and shape of population fronts.
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- 2024
7. A Hessian for Gaussian Mixture Likelihoods in Nonlinear Least Squares
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Korotkine, Vassili, Cohen, Mitchell, and Forbes, James Richard
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Computer Science - Robotics - Abstract
This paper proposes a novel Hessian approximation for Maximum a Posteriori estimation problems in robotics involving Gaussian mixture likelihoods. Previous approaches manipulate the Gaussian mixture likelihood into a form that allows the problem to be represented as a nonlinear least squares (NLS) problem. The resulting Hessian approximation used within NLS solvers from these approaches neglects certain nonlinearities. The proposed Hessian approximation is derived by setting the Hessians of the Gaussian mixture component errors to zero, which is the same starting point as for the Gauss-Newton Hessian approximation for NLS, and using the chain rule to account for additional nonlinearities. The proposed Hessian approximation results in improved convergence speed and uncertainty characterization for simulated experiments,and similar performance to the state of the art on real-world experiments. A method to maintain compatibility with existing solvers, such as ceres, is also presented. Accompanying software and supplementary material can be found at https://github.com/decargroup/hessian_sum_mixtures., Comment: 8 pages, 2 figures. Accepted to IEEE Robotics and Automation Letters
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- 2024
8. Forward-Backward Extended DMD with an Asymptotic Stability Constraint
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Lortie, Louis, Dahdah, Steven, and Forbes, James Richard
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Electrical Engineering and Systems Science - Systems and Control - Abstract
This paper presents a data-driven method to identify an asymptotically stable Koopman system from noisy data. In particular, the proposed approach combines approximations of the system's forward- and backward-in-time dynamics to reduce bias caused by noisy data while enforcing asymptotic stability. A Koopman model of an inherently asymptotically stable system can be unstable due to noisy data and a poor choice of lifting functions. To prevent identifying an unstable model, the proposed approach imposes an asymptotic stability constraint on the Koopman model. The proposed method is formulated as a semidefinite program and its performance is compared to state-of-the-art methods with a simulated Duffing oscillator dataset and experimental soft robot dataset., Comment: 20 pages, 7 figures
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- 2024
9. Optimal Robot Formations: Balancing Range-Based Observability and User-Defined Configurations
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Ahmed, Syed Shabbir, Shalaby, Mohammed Ayman, Ny, Jerome Le, and Forbes, James Richard
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Computer Science - Robotics - Abstract
This paper introduces a set of customizable and novel cost functions that enable the user to easily specify desirable robot formations, such as a ``high-coverage'' infrastructure-inspection formation, while maintaining high relative pose estimation accuracy. The overall cost function balances the need for the robots to be close together for good ranging-based relative localization accuracy and the need for the robots to achieve specific tasks, such as minimizing the time taken to inspect a given area. The formations found by minimizing the aggregated cost function are evaluated in a coverage path planning task in simulation and experiment, where the robots localize themselves and unknown landmarks using a simultaneous localization and mapping algorithm based on the extended Kalman filter. Compared to an optimal formation that maximizes ranging-based relative localization accuracy, these formations significantly reduce the time to cover a given area with minimal impact on relative pose estimation accuracy., Comment: 8 pages, 9 figures, submitted to IEEE International Conference on Intelligent Robots and Systems 2024
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- 2024
10. The Invariant Rauch-Tung-Striebel Smoother
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van der Laan, Niels, Cohen, Mitchell, Arsenault, Jonathan, and Forbes, James Richard
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Computer Science - Robotics - Abstract
This paper presents an invariant Rauch-Tung- Striebel (IRTS) smoother applicable to systems with states that are an element of a matrix Lie group. In particular, the extended Rauch-Tung-Striebel (RTS) smoother is adapted to work within a matrix Lie group framework. The main advantage of the invariant RTS (IRTS) smoother is that the linearization of the process and measurement models is independent of the state estimate resulting in state-estimate-independent Jacobians when certain technical requirements are met. A sample problem is considered that involves estimation of the three dimensional pose of a rigid body on SE(3), along with sensor biases. The multiplicative RTS (MRTS) smoother is also reviewed and is used as a direct comparison to the proposed IRTS smoother using experimental data. Both smoothing methods are also compared to invariant and multiplicative versions of the Gauss-Newton approach to solving the batch state estimation problem., Comment: 8 pages, 3 figures, published in Robotics and Automation Letters
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- 2024
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11. Navigation and Control of Unconventional VTOL UAVs in Forward-Flight with Explicit Wind Velocity Estimation
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Cohen, Mitchell and Forbes, James Richard
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Computer Science - Robotics - Abstract
This paper presents a solution for the state estimation and control problems for a class of unconventional vertical takeoff and landing (VTOL) UAVs operating in forward-flight conditions. A tightly-coupled state estimation approach is used to estimate the aircraft navigation states, sensor biases, and the wind velocity. State estimation is done within a matrix Lie group framework using the Invariant Extended Kalman Filter (IEKF), which offers several advantages compared to standard multiplicative EKFs traditionally used in aerospace and robotics problems. An SO(3)- based attitude controller is employed, leading to a single attitude control law without a separate sideslip control loop. A control allocator is used to determine how to use multiple, possibly redundant, actuators to produce the desired control moments. The wind velocity estimates are used in the attitude controller and the control allocator to improve performance. A numerical example is considered using a sample VTOL tailsitter-type UAV with four control surfaces. Monte-Carlo simulations demonstrate robustness of the proposed control and estimation scheme to various initial conditions, noise levels, and flight trajectories., Comment: 8 pages, 7 figures, published in Robotics and Automation Letters
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- 2024
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12. Laser-to-Vehicle Extrinsic Calibration in Low-Observability Scenarios for Subsea Mapping
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Hitchcox, Thomas and Forbes, James Richard
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Computer Science - Robotics - Abstract
Laser line scanners are increasingly being used in the subsea industry for high-resolution mapping and infrastructure inspection. However, calibrating the 3D pose of the scanner relative to the vehicle is a perennial source of confusion and frustration for industrial surveyors. This work describes three novel algorithms for laser-to-vehicle extrinsic calibration using naturally occurring features. Each algorithm makes a different assumption on the quality of the vehicle trajectory estimate, enabling good calibration results in a wide range of situations. A regularization technique is used to address low-observability scenarios frequently encountered in practice with large, rotationally stable subsea vehicles. Experimental results are provided for two field datasets, including the recently discovered wreck of the Endurance., Comment: 8 pages, 8 figures. Accepted for publication in IEEE Robotics and Automation Letters. Updated to include vol., no., and page nos
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- 2024
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13. Failure of Pavlik Harness Treatment in Infants Under 6 Months Old with Dislocated Hips: Short- and Intermediate-Term Results of Subsequent Treatment Modalities
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Imerci, Ahmet, Thacker, Mihir M., and Bowen, James Richard
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- 2024
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14. Options for Dynamic Similarity of Interacting Fluids, Elastic Solids and Rigid Bodies Undergoing Large Motions
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Liu, Huan, Jaykar, Kalpesh, Singh, Vinitendra, Kumar, Ankit, Sheehan, Kevin, Yip, Peter, Buskohl, Philip, and James, Richard D.
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- 2024
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15. navlie: A Python Package for State Estimation on Lie Groups
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Cossette, Charles Champagne, Cohen, Mitchell, Korotkine, Vassili, Bernal, Arturo del Castillo, Shalaby, Mohammed Ayman, and Forbes, James Richard
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Computer Science - Robotics - Abstract
The ability to rapidly test a variety of algorithms for an arbitrary state estimation task is valuable in the prototyping phase of navigation systems. Lie group theory is now mainstream in the robotics community, and hence estimation prototyping tools should allow state definitions that belong to manifolds. A new package, called navlie, provides a framework that allows a user to model a large class of problems by implementing a set of classes complying with a generic interface. Once accomplished, navlie provides a variety of on-manifold estimation algorithms that can run directly on these classes. The package also provides a built-in library of common models, as well as many useful utilities. The open-source project can be found at https://github.com/decargroup/navlie., Comment: 6 pages, 8 figures, presented at the 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
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- 2023
16. Bayesian Filtering for Homography Estimation
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Bernal, Arturo Del Castillo, Decoste, Philippe, and Forbes, James Richard
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Computer Science - Robotics - Abstract
This paper considers homography estimation in a Bayesian filtering framework using rate gyro and camera measurements. The use of rate gyro measurements facilitates a more reliable estimate of homography in the presence of occlusions, while a Bayesian filtering approach generates both a homography estimate along with an uncertainty. Uncertainty information opens the door to adaptive filtering approaches, post-processing procedures, and safety protocols. In particular, herein an iterative extended Kalman filter and an interacting multiple model (IMM) filter are tested using both simulated and experimental datasets. The IMM is shown to have good consistency properties and better overall performance when compared to the state-of-the-art homography nonlinear deterministic observer in both simulations and experiments., Comment: 8 pages and 6 figures, to be published in IEEE Robotics and Automation Letters
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- 2023
17. IMU Preintegration for Multi-Robot Systems in the Presence of Bias and Communication Constraints
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Shalaby, Mohammed Ayman, Cossette, Charles Champagne, Ny, Jerome Le, and Forbes, James Richard
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Computer Science - Robotics - Abstract
This document is in supplement to the paper titled "Multi-Robot Relative Pose Estimation and IMU Preintegration Using Passive UWB Transceivers", available at [1]. The purpose of this document is to show how IMU biases can be incorporated into the framework presented in [1], while maintaining the differential Sylvester equation form of the process model.
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- 2023
18. Magnetic Navigation using Attitude-Invariant Magnetic Field Information for Loop Closure Detection
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Pavlasek, Natalia, Cossette, Charles Champagne, Roy-Guay, David, and Forbes, James Richard
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Computer Science - Robotics - Abstract
Indoor magnetic fields are a combination of Earth's magnetic field and disruptions induced by ferromagnetic objects, such as steel structural components in buildings. As a result of these disruptions, pervasive in indoor spaces, magnetic field data is often omitted from navigation algorithms in indoor environments. This paper leverages the spatially-varying disruptions to Earth's magnetic field to extract positional information for use in indoor navigation algorithms. The algorithm uses a rate gyro and an array of four magnetometers to estimate the robot's pose. Additionally, the magnetometer array is used to compute attitude-invariant measurements associated with the magnetic field and its gradient. These measurements are used to detect loop closure points. Experimental results indicate that the proposed approach can estimate the pose of a ground robot in an indoor environment within meter accuracy.
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- 2023
19. Scaling Autoregressive Multi-Modal Models: Pretraining and Instruction Tuning
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Yu, Lili, Shi, Bowen, Pasunuru, Ramakanth, Muller, Benjamin, Golovneva, Olga, Wang, Tianlu, Babu, Arun, Tang, Binh, Karrer, Brian, Sheynin, Shelly, Ross, Candace, Polyak, Adam, Howes, Russell, Sharma, Vasu, Xu, Puxin, Tamoyan, Hovhannes, Ashual, Oron, Singer, Uriel, Li, Shang-Wen, Zhang, Susan, James, Richard, Ghosh, Gargi, Taigman, Yaniv, Fazel-Zarandi, Maryam, Celikyilmaz, Asli, Zettlemoyer, Luke, and Aghajanyan, Armen
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Computer Science - Machine Learning ,Computer Science - Computation and Language ,Computer Science - Computer Vision and Pattern Recognition - Abstract
We present CM3Leon (pronounced "Chameleon"), a retrieval-augmented, token-based, decoder-only multi-modal language model capable of generating and infilling both text and images. CM3Leon uses the CM3 multi-modal architecture but additionally shows the extreme benefits of scaling up and tuning on more diverse instruction-style data. It is the first multi-modal model trained with a recipe adapted from text-only language models, including a large-scale retrieval-augmented pre-training stage and a second multi-task supervised fine-tuning (SFT) stage. It is also a general-purpose model that can do both text-to-image and image-to-text generation, allowing us to introduce self-contained contrastive decoding methods that produce high-quality outputs. Extensive experiments demonstrate that this recipe is highly effective for multi-modal models. CM3Leon achieves state-of-the-art performance in text-to-image generation with 5x less training compute than comparable methods (zero-shot MS-COCO FID of 4.88). After SFT, CM3Leon can also demonstrate unprecedented levels of controllability in tasks ranging from language-guided image editing to image-controlled generation and segmentation.
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- 2023
20. Design of origami structures with curved tiles between the creases
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Liu, Huan and James, Richard D.
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Condensed Matter - Soft Condensed Matter - Abstract
An efficient way to introduce elastic energy that can bias an origami structure toward desired shapes is to allow curved tiles between the creases. The bending of the tiles supplies the energy and the tiles themselves may have additional functionality. In this paper, we present the theorem and systematic design methods for quite general curved origami structures that can be folded from a flat sheet, and we present methods to accurately find the stored elastic energy. Here the tiles are allowed to undergo curved isometric mappings, and the associated creases necessarily undergo isometric mappings as curves. These assumptions are consistent with a variety of practical methods for crease design. The h^3 scaling of the energy of thin sheets (h = thickness) spans a broad energy range. Different tiles in an origami design can have different values of h, and individual tiles can also have varying h. Following developments for piecewise rigid origami, we develop further the Lagrangian approach and the group orbit procedure in this context. We notice that some of the simplest designs that arise from the group orbit procedure for certain helical and conformal groups provide better matches to the buckling patterns observed in compressed cylinders and cones than known patterns.
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- 2023
21. On the kinetic description of the objective molecular dynamics
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James, Richard D., Qi, Kunlun, and Wang, Li
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Mathematics - Analysis of PDEs ,Mathematical Physics - Abstract
In this paper, we develop a multiscale hierarchy framework for objective molecular dynamics (OMD), a reduced order molecular dynamics with a certain symmetry, that connects it to the statistical kinetic equation, and the macroscopic hydrodynamic model. In the mesoscopic regime, we exploit two interaction scalings that lead, respectively, to either a mean-field type or to a Boltzmann type equation. It turns out that, under the special symmetry of OMD, the mean-field scaling results in vastly simplified dynamics that extinguishes the underlying molecular interaction rule, whereas the Boltzmann scaling yields a meaningful reduced model called the homo-energetic Boltzmann equation. At the macroscopic level, we derive the corresponding Euler and Navier-Stokes systems by conducting a detailed asymptotic analysis. The symmetry again significantly reduces the complexity of the resulting hydrodynamic systems.
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- 2023
22. Combining DVL-INS and Laser-Based Loop Closures in a Batch Estimation Framework for Underwater Positioning
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Al-Baali, Amro, Hitchcox, Thomas, and Forbes, James Richard
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Computer Science - Robotics - Abstract
Correcting gradual position drift is a challenge in long-term subsea navigation. Though highly accurate, modern inertial navigation system (INS) estimates will drift over time due to the accumulated effects of sensor noise and biases, even with acoustic aiding from a Doppler velocity log (DVL). The raw sensor measurements and estimation algorithms used by the DVL-aided INS are often proprietary, which restricts the fusion of additional sensors that could bound navigation drift over time. In this letter, the raw sensor measurements and their respective covariances are estimated from the DVL-aided INS output using semidefinite programming tools. The estimated measurements are then augmented with laser-based loop-closure measurements in a batch state estimation framework to correct planar position errors. The heading uncertainty from the DVL-aided INS is also considered in the estimation of the updated positions. The pipeline is tested in simulation and on experimental field data. The proposed methodology reduces the long-term navigation drift by more than 30 times compared to the DVL-aided INS estimate., Comment: 17 pages, 13 figures. Accepted for publication at the IEEE Journal of Oceanic Engineering
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- 2023
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23. Synthesizing Control Laws from Data using Sum-of-Squares Optimization
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Bramburger, Jason J., Dahdah, Steven, and Forbes, James Richard
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Mathematics - Optimization and Control ,Electrical Engineering and Systems Science - Systems and Control ,Mathematics - Dynamical Systems - Abstract
The control Lyapunov function (CLF) approach to nonlinear control design is well established. Moreover, when the plant is control affine and polynomial, sum-of-squares (SOS) optimization can be used to find a polynomial controller as a solution to a semidefinite program. This letter considers the use of data-driven methods to design a polynomial controller by leveraging Koopman operator theory, CLFs, and SOS optimization. First, Extended Dynamic Mode Decomposition (EDMD) is used to approximate the Lie derivative of a given CLF candidate with polynomial lifting functions. Then, the polynomial Koopman model of the Lie derivative is used to synthesize a polynomial controller via SOS optimization. The result is a flexible data-driven method that skips the intermediary process of system identification and can be applied widely to control problems. The proposed approach is used to successfully synthesize a controller to stabilize an inverted pendulum on a cart.
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- 2023
24. Cascaded Model Predictive Control of a Tandem-Rotor Helicopter
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Ahmed, Faraaz, Sobiesiak, Ludwik, and Forbes, James Richard
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Mathematics - Optimization and Control ,9306 (Primary), 4906 (Secondary) - Abstract
This letter considers cascaded model predictive control (MPC) as a computationally lightweight method for controlling a tandem-rotor helicopter. A traditional single MPC structure is split into separate outer and inner-loops. The outer-loop MPC uses an $SE_2(3)$ error to linearize the translational dynamics about a reference trajectory. The inner-loop MPC uses the optimal angular velocity sequence of the outer-loop MPC to linearize the rotational dynamics. The outer-loop MPC is run at a slower rate than the inner-loop allowing for longer prediction time and improved performance. Monte-Carlo simulations demonstrate robustness to model uncertainty and environmental disturbances. The proposed control structure is benchmarked against a single MPC algorithm where it shows significant improvements in position and velocity tracking while using significantly less computational resources., Comment: 6 pages, 3 figures
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- 2023
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25. Reimagining Retrieval Augmented Language Models for Answering Queries
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Tan, Wang-Chiew, Li, Yuliang, Rodriguez, Pedro, James, Richard, Lin, Xi Victoria, Halevy, Alon, and Yih, Scott
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Computer Science - Computation and Language ,Computer Science - Databases - Abstract
We present a reality check on large language models and inspect the promise of retrieval augmented language models in comparison. Such language models are semi-parametric, where models integrate model parameters and knowledge from external data sources to make their predictions, as opposed to the parametric nature of vanilla large language models. We give initial experimental findings that semi-parametric architectures can be enhanced with views, a query analyzer/planner, and provenance to make a significantly more powerful system for question answering in terms of accuracy and efficiency, and potentially for other NLP tasks
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- 2023
26. An Adaptive Graduated Nonconvexity Loss Function for Robust Nonlinear Least Squares Solutions
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Jung, Kyungmin, Hitchcox, Thomas, and Forbes, James Richard
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Computer Science - Robotics - Abstract
Many problems in robotics, such as estimating the state from noisy sensor data or aligning two point clouds, can be posed and solved as least-squares problems. Unfortunately, vanilla nonminimal solvers for least-squares problems are notoriously sensitive to outliers. As such, various robust loss functions have been proposed to reduce the sensitivity to outliers. Examples of loss functions include pseudo-Huber, Cauchy, and Geman-McClure. Recently, these loss functions have been generalized into a single loss function that enables the best loss function to be found adaptively based on the distribution of the residuals. However, even with the generalized robust loss function, most nonminimal solvers can only be solved locally given a prior state estimate due to the nonconvexity of the problem. The first contribution of this paper is to combine graduated nonconvexity (GNC) with the generalized robust loss function to solve least-squares problems without a prior state estimate and without the need to specify a loss function. Moreover, existing loss functions, including the generalized loss function, are based on Gaussian-like distribution. However, residuals are often defined as the squared norm of a multivariate error and distributed in a Chi-like fashion. The second contribution of this paper is to apply a norm-aware adaptive robust loss function within a GNC framework. The proposed approach enables a GNC formulation of a generalized loss function such that GNC can be readily applied to a wider family of loss functions. Furthermore, simulations and experiments demonstrate that the proposed method is more robust compared to non-GNC counterparts, and yields faster convergence times compared to other GNC formulations., Comment: Accepted to IEEE Transaction on Robotics 15 pages 11 figures
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- 2023
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27. Decentralized State Estimation: An Approach using Pseudomeasurements and Preintegration
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Cossette, Charles Champagne, Shalaby, Mohammed Ayman, Saussié, David, and Forbes, James Richard
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Computer Science - Robotics - Abstract
This paper addresses the problem of decentralized, collaborative state estimation in robotic teams. In particular, this paper considers problems where individual robots estimate similar physical quantities, such as each other's position relative to themselves. The use of pseudomeasurements is introduced as a means of modelling such relationships between robots' state estimates, and is shown to be a tractable way to approach the decentralized state estimation problem. Moreover, this formulation easily leads to a general-purpose observability test that simultaneously accounts for measurements that robots collect from their own sensors, as well as the communication structure within the team. Finally, input preintegration is proposed as a communication-efficient way of sharing odometry information between robots, and the entire theory is appropriate for both vector-space and Lie-group state definitions. To overcome the need for communicating preintegrated-covariance information, a deep autoencoder is proposed that reconstructs the covariance information from the inputs, hence further reducing the communication requirements. The proposed framework is evaluated on three different simulated problems, and one experiment involving three quadcopters., Comment: 15 pages, 13 figures, submitted to IJRR
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- 2023
28. Multi-Robot Relative Pose Estimation and IMU Preintegration Using Passive UWB Transceivers
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Shalaby, Mohammed Ayman, Cossette, Charles Champagne, Ny, Jerome Le, and Forbes, James Richard
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Computer Science - Robotics ,Electrical Engineering and Systems Science - Signal Processing - Abstract
Ultra-wideband (UWB) systems are becoming increasingly popular as a means of inter-robot ranging and communication. A major constraint associated with UWB is that only one pair of UWB transceivers can range at a time to avoid interference, hence hindering the scalability of UWB-based localization. In this paper, a ranging protocol is proposed that allows all robots to passively listen on neighbouring communicating robots without any hierarchical restrictions on the role of the robots. This is utilized to allow each robot to obtain more range measurements and to broadcast preintegrated inertial measurement unit (IMU) measurements for relative extended pose state estimation directly on SE_2(3). Consequently, a simultaneous clock-synchronization and relative-pose estimator (CSRPE) is formulated using an on-manifold extended Kalman filter (EKF) and is evaluated in simulation using Monte-Carlo runs for up to 7 robots. The ranging protocol is implemented in C on custom-made UWB boards fitted to 3 quadcopters, and the proposed filter is evaluated over multiple experimental trials, yielding up to 56% improvement in localization accuracy.
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- 2023
29. Retropharyngeal Hematoma Causing Airway Compromise After Tissue Plasminogen Activator Administration: A Case Report
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Provenza, Christian, Habermann, Arun Christian, Williams, Theron, Metter, Jeffrey, and Walker, James Richard
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retropharyngeal hematoma ,tissue plasminogen activator ,stroke ,airway ,hemorrhage - Abstract
Introduction: Tissue plasminogen activator (tPA), commonly used for treatment of acute ischemic stroke, is associated with life-threatening bleeding intracranially as well as surrounding the airway. Case Report: A 78-year-old year old male who presented with stroke symptoms and after tPA administration developed a retropharyngeal hematoma requiring intubation and surgical intervention. Conclusion: Numerous threats to the patient’s airway can develop after tPA administration. While angioedema is the most common cause, it is important to be prepared for other causes related to hemorrhage.
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- 2023
30. Closed-Loop Koopman Operator Approximation
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Dahdah, Steven and Forbes, James Richard
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Electrical Engineering and Systems Science - Systems and Control ,Computer Science - Machine Learning ,Mathematics - Dynamical Systems - Abstract
This paper proposes a method to identify a Koopman model of a feedback-controlled system given a known controller. The Koopman operator allows a nonlinear system to be rewritten as an infinite-dimensional linear system by viewing it in terms of an infinite set of lifting functions. A finite-dimensional approximation of the Koopman operator can be identified from data by choosing a finite subset of lifting functions and solving a regression problem in the lifted space. Existing methods are designed to identify open-loop systems. However, it is impractical or impossible to run experiments on some systems, such as unstable systems, in an open-loop fashion. The proposed method leverages the linearity of the Koopman operator, along with knowledge of the controller and the structure of the closed-loop system, to simultaneously identify the closed-loop and plant systems. The advantages of the proposed closed-loop Koopman operator approximation method are demonstrated in simulation using a Duffing oscillator and experimentally using a rotary inverted pendulum system. An open-source software implementation of the proposed method is publicly available, along with the experimental dataset generated for this paper., Comment: 13 pages, 11 figures, 3 tables, accepted for accepted for publication in Machine Learning: Science and Technology
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- 2023
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31. Theory of intermediate twinning and spontaneous polarization in the phase transformations of ferroelectric potassium sodium niobate
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Grekas, Georgios, Pop-Ghe, Patricia-Lia, Quandt, Eckhard, and James, Richard D.
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Condensed Matter - Materials Science - Abstract
Potassium sodium niobate is considered a prominent material system as a substitute for toxic lead-containing ferroelectric materials. It exhibits first-order phase transformations and ferroelectricity with potential applications ranging from energy conversion to innovative cooling technologies, hereby addressing urgent societal challenges. However, a major obstacle in the application of potassium sodium niobate is its multi-scale heterogeneity and the lack of understanding of its phase transition pathway and microstructure. This can be seen from the findings of Pop-Ghe 2021 et al. [1] which also reveal the occurrence of intermediate twinning during the phase transition. Here we show that intermediate twinning is a consequence of energy minimization. We employ a geometrically nonlinear electroelastic energy function for potassium sodium niobate, including the cubic-tetragonal-orthorhombic transformations and ferroelectricity. The construction of the minimizers is based on compatibility conditions which ensure continuous deformations and pole-free interfaces. These minimizers agree with the experimental observations, including laminates between the tetragonal variants under the cubic to tetragonal transformation, crossing twins under the tetragonal to orthorhombic transformation, intermediate twinning and spontaneous polarization. This shows how the full nonlinear electroelastic model provides a powerful tool in understanding, exploring and tailoring the electromechanical properties of complex ferroelectric ceramics.
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- 2023
32. Improving Self-Consistency in Underwater Mapping Through Laser-Based Loop Closure (Extended)
- Author
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Hitchcox, Thomas and Forbes, James Richard
- Subjects
Computer Science - Robotics - Abstract
Accurate, self-consistent bathymetric maps are needed to monitor changes in subsea environments and infrastructure. These maps are increasingly collected by underwater vehicles, and mapping requires an accurate vehicle navigation solution. Commercial off-the-shelf (COTS) navigation solutions for underwater vehicles often rely on external acoustic sensors for localization, however survey-grade acoustic sensors are expensive to deploy and limit the range of the vehicle. Techniques from the field of simultaneous localization and mapping, particularly loop closures, can improve the quality of the navigation solution over dead-reckoning, but are difficult to integrate into COTS navigation systems. This work presents a method to improve the self-consistency of bathymetric maps by smoothly integrating loop-closure measurements into the state estimate produced by a commercial subsea navigation system. Integration is done using a white-noise-on-acceleration motion prior, without access to raw sensor measurements or proprietary models. Improvements in map self-consistency are shown for both simulated and experimental datasets, including a 3D scan of an underwater shipwreck in Wiarton, Ontario, Canada., Comment: 26 pages, 18 figures. V2 correct Table III x2 parameter values, Table VIII 'INS' values, and equation A.28
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- 2023
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33. Know What You Don't Know: Consistency in Sliding Window Filtering with Unobservable States Applied to Visual-Inertial SLAM (Extended Version)
- Author
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Lisus, Daniil, Cohen, Mitchell, and Forbes, James Richard
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Computer Science - Robotics - Abstract
Estimation algorithms, such as the sliding window filter, produce an estimate and uncertainty of desired states. This task becomes challenging when the problem involves unobservable states. In these situations, it is critical for the algorithm to ``know what it doesn't know'', meaning that it must maintain the unobservable states as unobservable during algorithm deployment. This letter presents general requirements for maintaining consistency in sliding window filters involving unobservable states. The value of these requirements for designing navigation solutions is experimentally shown within the context of visual-inertial SLAM making use of IMU preintegration., Comment: Main paper accepted to Robotics and Automation Letters. Main paper has 8 pages, 3 figures. Supplemental materials are 6 pages, 0 figures after the main paper
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- 2022
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34. Reducing Two-Way Ranging Variance by Signal-Timing Optimization
- Author
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Shalaby, Mohammed Ayman, Cossette, Charles Champagne, Forbes, James Richard, and Ny, Jerome Le
- Subjects
Electrical Engineering and Systems Science - Signal Processing ,Computer Science - Robotics - Abstract
Time-of-flight-based ranging among transceivers with different clocks requires protocols that accommodate varying rates of the clocks. Double-sided two-way ranging (DS-TWR) is widely adopted as a standard protocol due to its accuracy; however, the precision of DS-TWR has not been clearly addressed. In this paper, an analytical model of the variance of DS-TWR is derived as a function of the user-programmed response delays, which is then compared to the Cramer-Rao Lower Bound (CRLB). This is then used to formulate an optimization problem over the response delays in order to maximize the information gained from range measurements. The derived analytical variance model and optimized protocol are validated experimentally with 2 ranging UWB transceivers, where 29 million range measurements are collected., Comment: 7 pages, 5 figures, accepted for publication at IEEE Transactions on Aerospace and Electronic Systems
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- 2022
35. Calibration and Uncertainty Characterization for Ultra-Wideband Two-Way-Ranging Measurements
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Shalaby, Mohammed Ayman, Cossette, Charles Champagne, Forbes, James Richard, and Ny, Jerome Le
- Subjects
Computer Science - Robotics ,Electrical Engineering and Systems Science - Signal Processing - Abstract
Ultra-Wideband (UWB) systems are becoming increasingly popular for indoor localization, where range measurements are obtained by measuring the time-of-flight of radio signals. However, the range measurements typically suffer from a systematic error or bias that must be corrected for high-accuracy localization. In this paper, a ranging protocol is proposed alongside a robust and scalable antenna-delay calibration procedure to accurately and efficiently calibrate antenna delays for many UWB tags. Additionally, the bias and uncertainty of the measurements are modelled as a function of the received-signal power. The full calibration procedure is presented using experimental training data of 3 aerial robots fitted with 2 UWB tags each, and then evaluated on 2 test experiments. A localization problem is then formulated on the experimental test data, and the calibrated measurements and their modelled uncertainty are fed into an extended Kalman filter (EKF). The proposed calibration is shown to yield an average of 46% improvement in localization accuracy. Lastly, the paper is accompanied by an open-source UWB-calibration Python library, which can be found at https://github.com/decargroup/uwb_calibration., Comment: 7 pages, 7 figures, to appear at the 2023 International Conference on Robotics and Automation (ICRA)
- Published
- 2022
36. A Hessian for Gaussian Mixture Likelihoods in Nonlinear Least Squares.
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Vassili Korotkine, Mitchell R. Cohen, and James Richard Forbes
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- 2024
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37. Reducing Two-Way Ranging Variance by Signal-Timing Optimization.
- Author
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Mohammed Ayman Shalaby, Charles Champagne Cossette, James Richard Forbes, and Jerome Le Ny
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- 2024
- Full Text
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38. Multi-robot Relative Pose Estimation and IMU Preintegration Using Passive UWB Transceivers.
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Mohammed Ayman Shalaby, Charles Champagne Cossette, Jerome Le Ny, and James Richard Forbes
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- 2024
- Full Text
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39. Laser-to-Vehicle Extrinsic Calibration in Low-Observability Scenarios for Subsea Mapping.
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Thomas Hitchcox and James Richard Forbes
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- 2024
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40. DIVE: Deep Inertial-Only Velocity Aided Estimation for Quadrotors.
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Angad Bajwa, Charles Champagne Cossette, Mohammed Ayman Shalaby, and James Richard Forbes
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- 2024
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41. SEC-seq: association of molecular signatures with antibody secretion in thousands of single human plasma cells
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Cheng, Rene Yu-Hong, de Rutte, Joseph, Ito, Cade Ellis K, Ott, Andee R, Bosler, Lucie, Kuo, Wei-Ying, Liang, Jesse, Hall, Brian E, Rawlings, David J, Di Carlo, Dino, and James, Richard G
- Subjects
Biochemistry and Cell Biology ,Biological Sciences ,Stem Cell Research ,Genetics ,Human Genome ,Stem Cell Research - Nonembryonic - Human ,Biotechnology ,2.1 Biological and endogenous factors ,Aetiology ,Underpinning research ,1.1 Normal biological development and functioning ,Humans ,Plasma Cells ,B-Lymphocytes ,Cell Membrane ,Biomarkers ,Immunoglobulin G - Abstract
The secreted products of cells drive many functions in vivo; however, methods to link this functional information to surface markers and transcriptomes have been lacking. By accumulating secretions close to secreting cells held within cavity-containing hydrogel nanovials, we demonstrate workflows to analyze the amount of IgG secreted from single human B cells and link this information to surface markers and transcriptomes from the same cells. Measurements using flow cytometry and imaging flow cytometry corroborate the association between IgG secretion and CD38/CD138. By using oligonucleotide-labeled antibodies we find that upregulation of pathways for protein localization to the endoplasmic reticulum and mitochondrial oxidative phosphorylation are most associated with high IgG secretion, and uncover surrogate plasma cell surface markers (e.g., CD59) defined by the ability to secrete IgG. Altogether, this method links quantity of secretion with single-cell sequencing (SEC-seq) and enables researchers to fully explore the links between genome and function, laying the foundation for discoveries in immunology, stem cell biology, and beyond.
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- 2023
42. Performance Evaluation of 3D Keypoint Detectors and Descriptors on Coloured Point Clouds in Subsea Environments
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Jung, Kyungmin, Hitchcox, Thomas, and Forbes, James Richard
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Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Robotics - Abstract
The recent development of high-precision subsea optical scanners allows for 3D keypoint detectors and feature descriptors to be leveraged on point cloud scans from subsea environments. However, the literature lacks a comprehensive survey to identify the best combination of detectors and descriptors to be used in these challenging and novel environments. This paper aims to identify the best detector/descriptor pair using a challenging field dataset collected using a commercial underwater laser scanner. Furthermore, studies have shown that incorporating texture information to extend geometric features adds robustness to feature matching on synthetic datasets. This paper also proposes a novel method of fusing images with underwater laser scans to produce coloured point clouds, which are used to study the effectiveness of 6D point cloud descriptors.
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- 2022
43. System Identification and Two-Degree-of-Freedom Control of Nonlinear, Viscoelastic Tissues
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Bianco, Amanda, Zonis, Raphael, Lauzon, Anne-Marie, Forbes, James Richard, and Ijpma, Gijs
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Electrical Engineering and Systems Science - Systems and Control ,Quantitative Biology - Tissues and Organs - Abstract
Objective: This paper presents a force control scheme for brief isotonic holds in an isometrically contracted muscle tissue, with minimal overshoot and settling time to measure its shortening velocity, a key parameter of muscle function. Methods: A two-degree-of-freedom control configuration, formed by a feedback controller and a feedforward controller, is explored. The feedback controller is a proportional-integral controller and the feedforward controller is designed using the inverse of a control-oriented model of muscle tissue. A generalized linear model and a nonlinear model of muscle tissue are explored using input-output data and system identification techniques. The force control scheme is tested on equine airway smooth muscle and its robustness confirmed with murine flexor digitorum brevis muscle. Results: Performance and repeatability of the force control scheme as well as the number of inputs and level of supervision required from the user were assessed with a series of experiments. The force control scheme was able to fulfill the stated control objectives in most cases, including the requirements for settling time and overshoot. Conclusion: The proposed control scheme is shown to enable automation of force control for characterizing muscle mechanics with minimal user input required. Significance: This paper leverages an inversion-based feedforward controller based on a nonlinear physiological model in a system identification context that is superior to classic linear system identification. The control scheme can be used as a steppingstone for generalized control of nonlinear, viscoelastic materials., Comment: 9 pages, 11 figures, accepted for publication in IEEE Transactions on Biomedical Engineering
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- 2022
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44. Relative Position Estimation in Multi-Agent Systems Using Attitude-Coupled Range Measurements
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Shalaby, Mohammed, Cossette, Charles Champagne, Forbes, James Richard, and Ny, Jerome Le
- Subjects
Computer Science - Robotics - Abstract
The ability to accurately estimate the position of robotic agents relative to one another, in possibly GPS-denied environments, is crucial to execute collaborative tasks. Inter-agent range measurements are available at a low cost, due to technologies such as ultra-wideband radio. However, the task of three-dimensional relative position estimation using range measurements in multi-agent systems suffers from unobservabilities. This letter presents a sufficient condition for the observability of the relative positions, and satisfies the condition using a simple framework with only range measurements, an accelerometer, a rate gyro, and a magnetometer. The framework has been tested in simulation and in experiments, where 40-50 cm positioning accuracy is achieved using inexpensive off-the-shelf hardware., Comment: 7 pages, 10 figures, published in IEEE Robotics and Automation Letters
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- 2022
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45. A note on the relationship between action accessible and weakly action representable categories
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Gray, James Richard Andrew
- Subjects
Mathematics - Category Theory - Abstract
The main purpose of this paper is to show that the converse of the known implication weakly action representable implies action accessible is false. In particular we show that both action accessibility, as well as the (at least formally stronger) condition requiring the existence of all normalizers do not imply weakly-action-representability even for varieties. In addition we show that in contrast to both action accessibility and the condition requiring the existence of all normalizers, weakly-action representability is not necessarily inherited by Birkoff subcategories.
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- 2022
46. A note on the Huq-commutativity of normal monomorphisms
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Gray, James Richard Andrew and Janelidze-Gray, Tamar
- Subjects
Mathematics - Category Theory - Abstract
We give an alternative criteria for when a pair of Bourn-normal monomorphisms Huq-commute in a unital category. We use this to prove that in a unital category, in which a morphism is a monomorphism if and only if its kernel is zero morphism, a pair of Bourn-normal monomorphisms with the same codomain Huq-commute as soon as they have trivial pullback. As corollaries we show that several facts known only in the protomodular context are in fact true in more general contexts.
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- 2022
47. Mind the Gap: Norm-Aware Adaptive Robust Loss for Multivariate Least-Squares Problems
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Hitchcox, Thomas and Forbes, James Richard
- Subjects
Computer Science - Robotics - Abstract
Measurement outliers are unavoidable when solving real-world robot state estimation problems. A large family of robust loss functions (RLFs) exists to mitigate the effects of outliers, including newly developed adaptive methods that do not require parameter tuning. All of these methods assume that residuals follow a zero-mean Gaussian-like distribution. However, in multivariate problems the residual is often defined as a norm, and norms follow a Chi-like distribution with a non-zero mode value. This produces a "mode gap" that impacts the convergence rate and accuracy of existing RLFs. The proposed approach, "Adaptive MB," accounts for this gap by first estimating the mode of the residuals using an adaptive Chi-like distribution. Applying an existing adaptive weighting scheme only to residuals greater than the mode leads to more robust performance and faster convergence times in two fundamental state estimation problems, point cloud alignment and pose averaging., Comment: 8 pages, 4 figures. This paper has been accepted for publication in IEEE Robotics and Automation Letters. V2: Update weighting in (13), (28) and re-run results. Hypothesis, methodology, and general findings remain unchanged. Update Sec. II-A to reference IRLS, and update citation [11] accordingly. Include acknowledgement to Mitchell Cohen. V3: Update Section II-A to least-squares
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- 2022
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48. Model Predictive Control of a Tandem-Rotor Helicopter With a Nonuniformly Spaced Prediction Horizon
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Ahmed, Faraaz, Sobiesiak, Ludwik, and Forbes, James Richard
- Subjects
Mathematics - Optimization and Control ,9306 (Primary), 4906 (Secondary) - Abstract
This letter considers model predictive control of a tandem-rotor helicopter. The error is formulated using the matrix Lie group $SE_2(3)$. A reference trajectory to a target is calculated using a quartic guidance law, leveraging the differentially flat properties of the system, and refined using a finite-horizon linear quadratic regulator. The nonlinear system is linearized about the reference trajectory enabling the formulation of a quadratic program with control input, attitude keep-in zone, and attitude error constraints. A non-uniformly spaced prediction horizon is leveraged to capture the multi-timescale dynamics while keeping the problem size tractable. Monte-Carlo simulations demonstrate robustness of the proposed control structure to initial conditions, model uncertainty, and environmental disturbances., Comment: 6 pages, 5 figures
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- 2022
- Full Text
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49. Optimal Multi-robot Formations for Relative Pose Estimation Using Range Measurements
- Author
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Cossette, Charles Champagne, Shalaby, Mohammed Ayman, Saussie, David, Ny, Jerome Le, and Forbes, James Richard
- Subjects
Computer Science - Robotics - Abstract
In multi-robot missions, relative position and attitude information between agents is valuable for a variety of tasks such as mapping, planning, and formation control. In this paper, the problem of estimating relative poses from a set of inter-agent range measurements is investigated. Specifically, it is shown that the estimation accuracy is highly dependent on the true relative poses themselves, which prompts the desire to find multi-agent formations that provide the best estimation performance. By direct maximization of Fischer information, it is shown in simulation and experiment that large improvements in estimation accuracy can be obtained by optimizing the formation geometry of a team of robots., Comment: 7 pages, 8 figures, submitted to International Conference on Intelligent Robots and Systems
- Published
- 2022
50. Informing the pandemic response: the role of the WHO’s COVID-19 Weekly Epidemiological Update
- Author
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Maria D Van Kerkhove, Mahmoud Hassan, Ibrahima Socé Fall, Olivier Le Polain de Waroux, Boris Igor Pavlin, Sandra Adele, Kazuki Shimizu, Oliver Morgan, Daniel Feikin, Lorenzo Subissi, Richard G Pebody, Masaya Kato, Opeayo Ogundiran, Ana Riviere-Cinnamond, Tshewang Dorji, Ingrid Hammermeister Nezu, Friday Idoko, Tamano Matsui, Silviu Ciobanu, Juniorcaius Ikejezie, Blanche Johanna Greene-Cramer, Tondri Noe Guinko, Samuel Mesfin, Harsh Lata, Alessandro Miglietta, Yurie Izawa, Aura Rocio Escobar Corado Waeber, Anahi Rico Chinchilla, Adedoyin Awofisayo-Okuyelu, Esther Hamblion, Melissa M Higdon, Ayse Acma, Samuel Moro, Homa Attar Cohen, Mary Anissa Sinnathamby, James Richard Otieno, Yosef Temre, Brian Ngongheh Ajong, Bernadette Basuta Mirembe, Vaishali Sodagar, Craig Schultz, Joao Muianga, Stéphane De Barros, Yeowon Jin, Shagun Khare, Marcia Poole, Nyka Alexander, Manilay Phengxay, Emilie Peron, Brett Nicholas Archer, Zyleen Alnashir Kassamali, and Abdi Mahamud
- Subjects
Medicine (General) ,R5-920 ,Infectious and parasitic diseases ,RC109-216 - Abstract
On 31 December 2019, the Municipal Health Commission of Wuhan, China, reported a cluster of atypical pneumonia cases. On 5 January 2020, the WHO publicly released a Disease Outbreak News (DON) report, providing information about the pneumonia cases, implemented response interventions, and WHO’s risk assessment and advice on public health and social measures. Following 9 additional DON reports and 209 daily situation reports, on 17 August 2020, WHO published the first edition of the COVID-19 Weekly Epidemiological Update (WEU). On 1 September 2023, the 158th edition of the WEU was published on WHO’s website, marking its final issue. Since then, the WEU has been replaced by comprehensive global epidemiological updates on COVID-19 released every 4 weeks. During the span of its publication, the webpage that hosts the WEU and the COVID-19 Operational Updates was accessed annually over 1.4 million times on average, with visits originating from more than 100 countries. This article provides an in-depth analysis of the WEU process, from data collection to publication, focusing on the scope, technical details, main features, underlying methods, impact and limitations. We also discuss WHO’s experience in disseminating epidemiological information on the COVID-19 pandemic at the global level and provide recommendations for enhancing collaboration and information sharing to support future health emergency responses.
- Published
- 2024
- Full Text
- View/download PDF
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