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The ability of ankle rehabilitation robots to accurately mimicking the actual human ankle motion is an important judgment basis for robot-assisted rehabilitation training. This paper proposes an evaluation index and mechanism parameter optimization method based on ankle-foot motion trajectory by exploring the human ankle-foot motion principle. First, the ankle UR equivalent model and a 3-degree-of-freedom (DOF) parallel ankle rehabilitation robot are described. Second, the ankle-foot motion data are measured by the body surface marker method, which proved the coupling of ankle-foot motion. Then, a new evaluation index, the ankle-foot motion comfort zone, is proposed, which is essentially the superimposed ankle-foot motion trajectory measured about 3-5 mm wide. Third, a mechanism parameter optimization method, is proposed in terms of the ankle-foot motion comfort zone as the evaluation index, which is applied to the 3-DOF parallel ankle rehabilitation robot, and the optimization results proved the feasibility of the method. Finally, the optimized rehabilitation robot is fitted with different ankle motions, and a prototype model is designed for kinematics simulation, which verifies the adaptability of the optimization method. This study provides a theoretical basis for the configuration design of ankle rehabilitation robots and provides a new direction for the optimization of the mechanism parameters., (Copyright © 2023 by ASME.)

Simultaneously guaranteeing material removal accuracy and surface quality of robotic grinding is crucial. However, existing studies of robotic grinding process optimization have mainly focused on a single indicator that solely considers contour error or surface roughness, while studies that simultaneously investigate the impact of contact force, spindle speed, feed rate, inclination angle, and path space on the material removal profile (MRP) and the surface roughness are lacking. This paper proposes a hybrid optimization method that considers dimensional accuracy and surface quality constraints. First, an MRP model that considers the coupling influence of the contact force, spindle speed, feed rate, and inclination angle is presented. Then, a surface roughness model that considers the inclination angle is established. Finally, the contact force, feed rate, inclination angle, and path space are simultaneously optimized to satisfy the hybrid constraints of MRP accuracy and surface roughness. The proposed method ensures maximum grinding efficiency while satisfying dimensional accuracy and surface quality constraints. The proposed method is verified on an industrial robotics grinding system with a pneumatic force-controlled actuator. The results show that the proposed method has higher profile accuracy and lower surface roughness than traditional methods. [ABSTRACT FROM AUTHOR]

Vision-based robots have been utilized for pick-and-place operations by their ability to find object poses. As they progress into handling a variety of objects with cluttered state, more flexible and lightweight operations have been presented. In this paper, an autonomous robotic bin-picking platform is proposed. It combines human demonstration with a collaborative robot for the flexibility of the objects and YOLOv5 neural network model for faster object localization without prior computer-aided design models or dataset in the training. After a simple human demonstration of which target object to pick and place, the raw color and depth images were refined, and the one on top of the bin was utilized to create synthetic images and annotations for the YOLOv5 model. To pick up the target object, the point cloud was lifted using the depth data corresponding to the result of the trained YOLOv5 model, and the object pose was estimated by matching them with Iterative Closest Points (ICP) algorithm. After picking up the target object, the robot placed it where the user defined it in the previous human demonstration stage. From the result of experiments with four types of objects and four human demonstrations, it took a total of 0.5 s to recognize the target object and estimate the object pose. The success rate of object detection was 95.6%, and the pick-and-place motion of all the found objects was successful. [ABSTRACT FROM AUTHOR]

Robotic machining efficiency and accuracy are constrained by milling vibrations and chatter. The dynamic characteristics of robots are highly influenced by their poses. Consequently, it is crucial to obtain the robot's dynamic characteristics in any given pose to mitigate vibrations and prevent chatter during large-range machining. This paper proposes an incremental self-excitation method for effectively identifying low-frequency frequency response functions (FRF) of milling robots. By attaching a mass block at the robot's end, a fully knowable and controllable excitation increment can be achieved, overcoming the shortcoming of traditional self-excitation methods in capturing the dynamic compliance magnitude. By employing suitable trajectory programming, this method can be executed automatically in the desired poses without the need for manual operations. First, the impulse (moment) of the incremental self-excitation is modeled based on momentum theorem, and the association model of the pulse response increment with the incremental self-excitation is established. To address the issue of sensitivity to noise in the FRF calculation process, the incremental self-excitation is assumed to be a Gaussian pulse, and its identification method is provided. Subsequently, the dimensionality requirement for identifying the nine-item (direct and cross) FRFs is effectively reduced using the modal directionality of milling robots, and the corresponding FRF calculation method is proposed. The rationality of the simplifications and assumptions employed in this method is validated through experiments and calculations. The experimental results in several robot poses show that the proposed method can effectively identify all the direct and cross FRFs in the low-frequency band. [ABSTRACT FROM AUTHOR]

Cutting force identification is critical to improving industrial robot performance and reducing machining vibration. However, most indirect identification methods of cutting force are not applicable since the modal parameters of the robotic milling system vary with the robot pose. This paper presents a novel pose-dependent method to identify the cutting force using the acceleration signal generated by robotic milling. First, the modal parameters at different machining points are employed as a training dataset to develop the Gaussian Process Regression (GPR) model. Next, the modal parameters predicted by the GPR model are employed to optimize the cutting force estimation based on the minimum variance unbiased estimate method. Then, the Kalman filter method is employed to update the covariance matrix of the cutting force identification error and the state estimation error. Lastly, the effectiveness of the proposed method is verified with robotic milling experiments, and the results show that the identification error and time are acceptable under the condition of variable robot pose. [ABSTRACT FROM AUTHOR]

Robotic flat-end milling of complex surfaces offers advantages such as high flexibility and high machining efficiency. In the process of planning the toolpath based on the cutter contact path, the robot functional redundancy and the tool orientation need to be solved carefully. This paper presents a posture optimization method for robotic flat-end milling. Taking the weighted sum of the machining width and the toolpath smoothness performance criterion as the objective function, an optimization model considering the joint limits and gouging avoidance is established. An efficient algorithm based on sequential quadratic programming is proposed to solve this nonconvex problem. During the execution of the algorithm, the machining width is efficiently calculated by an iterative method based on conformal geometric algebra, while its derivatives are approximated analytically. Simulations and experiments demonstrate that the presented technique can resolve the tool axis direction and the robot redundancy effectively to increase the machining width and improve the toolpath smoothness, thus reducing the time for machining and improving the surface quality. [ABSTRACT FROM AUTHOR]

Disassembly is an essential process for the recovery of end-of-life (EOL) electronics in remanufacturing sites. Nevertheless, the process remains labor-intensive due to EOL electronics' high degree of uncertainty and complexity. The robotic technology can assist in improving disassembly efficiency; however, the characteristics of EOL electronics pose difficulties for robot operation, such as removing small components. For such tasks, detecting small objects is critical for robotic disassembly systems. Screws are widely used as fasteners in ordinary electronic products while having small sizes and varying shapes in a scene. To enable robotic systems to disassemble screws, the location information and the required tools need to be predicted. This paper proposes a computer vision framework for detecting screws and recommending related tools for disassembly. First, a YOLOv4 algorithm is used to detect screw targets in EOL electronic devices and a screw image extraction mechanism is executed based on the position coordinates predicted by YOLOv4. Second, after obtaining the screw images, the EfficientNetv2 algorithm is applied for screw shape classification. In addition to proposing a framework for automatic small-object detection, we explore how to modify the object detection algorithm to improve its performance and discuss the sensitivity of tool recommendations to the detection predictions. A case study of three different types of screws in EOL electronics is used to evaluate the performance of the proposed framework. [ABSTRACT FROM AUTHOR]

This paper presents a Gaussian process regression (GPR)-based approach to model the dynamic properties of a six-degree-of-freedom (6-DOF) industrial robot within its workspace. Discretely sampled modal parameters (modal frequency, modal stiffness, modal damping coefficient) of the robot structure determined through experimental modal analysis are used to develop the GPR model, which is then evaluated for its ability to accurately predict the modal parameters at different points in the workspace. The validation results show that the model captures the significant trends in the modal parameters within the sampling space but exhibits greater errors in regions further from the robot base. The results of the GPR model are also compared with those derived from an analytical model of the robot tool tip dynamics. The analytical model is found to overestimate the robot's stiffness, especially in extended arm configurations, and to underestimate the natural frequency. The average peak-to-valley vibrations predicted by the GPR model during robotic end milling are compared with experimental results. The model-predicted peak-to-valley vibrations follow the measured values with a maximum error of 0.028 mm in the wall and floor surface directions. The results show that the GPR model presented in this paper can serve as a useful tool for understanding and optimizing the tool tip vibrations produced in robotic milling. [ABSTRACT FROM AUTHOR]

Tactile sensors are essential to robot hands that deal with various objects and interact with the environment. Soft tactile sensors are especially important to capture tactile information about delicate, irregular-shaped, or unknown objects. This paper introduces a soft tactile sensor that can simultaneously estimate the contact force, contact feature, and contact point. Inspired by multifunctional human skin, the proposed design has a dual-layer structure and is multifunctional. The top layer consists of a group of sensing elements that detect the contact location and contact feature enhanced by the bagging classifier based on the k-nearest neighbors. The sensor elements were biomimetically and analytically designed as a pyramid shape that mimicked the mountain ridge-like structure in human skin to improve sensitivity. The bottom layer was made by a piece of Velostat sandwiched between conductive fabrics that can measure the contact force. The relationship between the sensing voltage and the contact force was modeled by the Nadaraya-Watson regressor. The performance of the proposed sensor was verified by a repeatability test. Furthermore, we demonstrated the effectiveness of the proposed sensor on a robotic gripper. The experimental results show that this sensor is able to detect contact information of fragile objects. [ABSTRACT FROM AUTHOR]

This paper presents the design and analysis of a three-fingered deployable metamorphic robotic grasper for manipulating large-scale unknown objects. This grasper is composed of three fingers and a single-mobility umbrella-shaped palmar mechanism. First, the mechanism-design of the grasper is introduced and the metamorphic-motion process is analyzed, followed by the structural optimization, the finger with three modules can be deployed from 111.5 mm to 304 mm, and the good deploy/fold ratio can reach 2.73. This equips the grasper with a compact folded configuration and a large deployed configuration. Second, kinematic models of the deployment motion and grasping motion are independently established, and kinematic analysis is conducted. To further illustrate kinematic performance, kinematic simulation for the grasper is then performed. Third, the condition of the stable grasp is analyzed; trajectory planning of the grasper based on an S-shaped acceleration and deceleration function algorithm is then carried out. Fourth, a control system is designed and a physical prototype is fabricated. Grasping experiments are then conducted to prove the ability of the grasper to grasp objects of various sizes and shapes. [ABSTRACT FROM AUTHOR]

In structural health monitoring (SHM) applications carried out by mobile robots, the precise locating of the SHM robot is essential for accurate detection and quantification of defects. The traditional dead reckoning (DR) approach can only provide local position in the horizon, which is not enough for SHM applications in three dimensions in large buildings. In this paper, a new robot positioning algorithm for active building structural defect detection and localization is proposed. The two-stage robot positioning scheme is designed through the self-misalignment calibration and the positioning during SHM task stages, fusing the absolute and relative measurements. In order to overcome the drawback of the DR algorithm, in the full analysis of existing localization mode that can be applied to mobile robots, this paper adopted the inertial navigation system (INS) approach to measure the absolute motion information of a moving robot. On this basis, through the transformation between the absolute positioning coordinates and the local positioning coordinates of buildings, the mobile robot's optimal trajectory on building surface was designed for self-calibration of coordinate misalignments. The proposed method could effectively achieve the robot local positioning in building coordinate frame by fusing the external relative assistant measurements with absolute measurement. By using the designed strategies, the coordinate misalignment can also be self-calibrated effectively, improving local positioning accuracy. [ABSTRACT FROM AUTHOR]

Hybrid zero dynamics (HZD) control creates dynamically stable gaits by driving a hybrid robot model toward an optimally generated state-dependent reference signal. This paper presents the first application of HZD to an underactuated lower-limb exoskeleton for gait guidance. A phase-based reference gait is generated to follow a nominal walking pattern. Simulation results using a phase-based proportional-derivative (PD) controller validate that stable periodic gait similar to nominal gait is possible for the identified human-exoskeleton model. For hardware application, a bilateral mixing strategy is taken to accommodate the presence of the double support phase, which was assumed to be instantaneous in the hybrid model. A treadmill experiment is conducted with a healthy subject using the Indego Explorer exoskeleton. Comparing the recorded gait to the optimal phase-based reference, the root-mean-square joint tracking errors (RMSE) are 2.87 deg, 2.79 deg, 3.20 deg, and 11.0 deg at the stance hip, stance knee, swing hip, and swing knee, respectively. Similarly, compared to the commanded reference, the RMSE are 2.04 deg, 4.40 deg, 4.58 deg, and 6.83 deg, respectively. A second experiment was conducted wherein the treadmill speed varied from 0.3 to 0.5 m/s. The results show how the HZD controller exhibits remarkable flexibility and robustness for multiple walking speeds and grants the operator greater level of volitional control due to the time-invariant, phase-based nature of the implementation. Taken altogether, the presented results suggest that HZD control can serve as a rehabilitative control method capable of providing gait guidance in underactuated exoskeleton systems. [ABSTRACT FROM AUTHOR]

The design of cleaning and maintenance (CaM) robots is generally limited by their fixed morphologies, resulting in limited functions and modes of operation. Contrary to fixed shape robots, the design of reconfigurable robots presents unique challenges in designing their system, subsystems, and functionalities with the scope for innovative operational scenarios and achieving high performance in multiple modalities without compromise. This paper proposes a heuristic framework using three layers, namely input, formulation, and output layer, for designing reconfigurable robots with the aid of established transformation principles including expand/collapse, expose/cover, and fuse/divide observed in several products, services, and systems. We apply this heuristic framework approach to the novel design of a pavement CaM robotic system and subsystems, namely, (i) varying footprint, (ii) transmission, (iii) outer skin or cover, (iv) storage bin, (v) surface cleaning, and (vi) vacuum/suction and blowing. The advances in the design method using the heuristic approach are demonstrated by developing an innovative reconfigurable design for the CaM task. Kinematic analysis and control architecture enables the unique locomotion behavior and gaits, namely, (a) static reconfiguration and (b) reconfiguration while locomotion, supported by the control architecture. Experiments were conducted, and outcomes were discussed along with the failure mode analysis to support the design robustness and limitations through the observations made from the development to testing phase over one year. A detailed video demonstrating the design capabilities is linked. [ABSTRACT FROM AUTHOR]

In this paper, a novel four degrees-of-freedom (4DOF) articulated parallel forceps mechanism with a large orientation workspace (± 90 deg in pitch and yaw, 360 deg in roll rotations) is presented for robotic minimally invasive surgery. The proposed 3RSR-1UUP parallel mechanism utilizes a UUP center leg that can convert thrust motion of the 3RSR mechanism into gripping motion. This design eliminates the need for an additional gripper actuator, but also introduces the problem of unintentional gripper opening/closing due to parasitic motion of the 3RSR mechanism. Here, position kinematics of the proposed mechanism, including the workspace, is analyzed in detail, and a solution to the parasitic motion problem is provided. Human-in-the-loop simulations with a haptic interface are also performed to confirm the feasibility of the proposed design. [ABSTRACT FROM AUTHOR]

In robotics, the risk of collisions is present both in industrial applications and in remote handling. If a collision occurs, the impact may damage both the robot and external equipment, which may result in successive imprecise robot tasks or line stops, reducing robot efficiency. As a result, appropriate collision avoidance algorithms should be used or, if it is not possible, the robot must be able to react to impacts reducing the contact forces. For this purpose, this paper focuses on the development of a special end-effector that can withstand impacts. It is able to protect the robot from impulsive forces caused by collisions of the end-effector, but it has no effect on possible collisions between the links and obstacles. The novel end-effector is based on a bi-stable mechanism that decouples the dynamics of the end-effector from the dynamics of the robot. The intrinsically nonlinear behavior of the end-effector is investigated with the aid of numerical simulations. The effect of design parameters and operating conditions are analyzed and the interaction between the functioning of the bi-stable mechanism and the control system is studied. In particular, the effect of the mechanism in different scenarios characterized by different robot velocities is shown. Results of numerical simulations assess the validity of the proposed end-effector, which can lead to large reductions in impact forces. Numerical results are validated by means of specific laboratory tests. [ABSTRACT FROM AUTHOR]

Image feature-based localization and mapping applications useful in field robotics are considered in this paper. Exploiting the continuity of image features and building upon the tracking algorithms that use point correspondences to provide an instantaneous localization solution, an extended Kalman filtering (EKF) approach is formulated for estimation of the rigid body motion of the camera coordinates with respect to the world coordinate system. Recent results by the authors in quantifying uncertainties associated with the feature tracking methods form the basis for deriving scene-dependent measurement error statistics that drive the optimal estimation approach. It is shown that the use of certain relative motion models between a static scene and the moving target can be recast as a recursive least squares problem and admits an efficient solution to the relative motion estimation problem that is amenable to real-time implementations on board mobile computing platforms with computational constraints. The utility of the estimation approaches developed in the paper is demonstrated using stereoscopic terrain mapping experiments carried out using mobile robots. The map uncertainties estimated by the filter are utilized to establish the registration of the local maps into the global coordinate system. [ABSTRACT FROM AUTHOR]

This paper presents the design, modeling, and control of a three-joint robotic fish propelled by a double-slider-crank (DSC) driven caudal fin. DSC is a mechanism that can use one direct current motor to achieve oscillating foil propulsion. Its design is guided by a traveling wave equation that mimics a fish's undulatory locomotion. After multiple tests, the robotic fish displayed good performance in mimicking a real fish's swimming motion. DSC mechanism is proven to be an effective propulsion technique for a robotic fish. With the help of another servomotor at the first joint of the fish's tail, the robotic fish can have a two-dimensional free-swimming capability. In experiments, the robotic fish can achieve a swimming speed of 0.35 m/s at 3 Hz, equivalent to 0.98 body length (BL) per second. Its steering rate is proportional to a bias angle. The DSC benefits the control of the robotic fish by independently adjusting its steering and swimming speed. This characteristic is studied in a hydrodynamic model that derives the thrust within a DSC frame. Besides the dynamic model, a semiphysics-based and data-driven linear model is established to connect bias angle to robotic fish's heading angle. The linear model is used for designing an observed-state feedback control control, and the controller has been examined in simulation and experiments. [ABSTRACT FROM AUTHOR]

Accurate knowledge of body segment inertia parameters (BSIP) improves the assessment of dynamic analysis based on biomechanical models, which is of paramount importance in fields such as sport activities or impact crash test. Early approaches for BSIP identification rely on the experiments conducted on cadavers or through imaging techniques conducted on living subjects. Recent approaches for BSIP identification rely on inverse dynamic modeling. However, most of the approaches are focused on the entire body, and verification of BSIP for dynamic analysis for distal segment or chain of segments, which has proven to be of significant importance in impact test studies, is rarely established. Previous studies have suggested that BSIP should be obtained by using subject-specific identification techniques. To this end, our paper develops a novel approach for estimating subject-specific BSIP based on static and dynamics identification models (SIM, DIM). We test the validity of SIM and DIM by comparing the results using parameters obtained from a regression model proposed by De Leva (1996, "Adjustments to Zatsiorsky-Seluyanov's Segment Inertia Parameters," J. Biomech., 29(9), pp. 1223-1230). Both SIM and DIM are developed considering robotics formalism. First, the static model allows the mass and center of gravity (COG) to be estimated. Second, the results from the static model are included in the dynamics equation allowing us to estimate the moment of inertia (MOI). As a case study, we applied the approach to evaluate the dynamics modeling of the head complex. Findings provide some insight into the validity not only of the proposed method but also of the application proposed by De Leva (1996, "Adjustments to Zatsiorsky-Seluyanov's Segment Inertia Parameters," J. Biomech., 29(9), pp. 1223-1230) for dynamic modeling of body segments.

Passive dynamic systems have the advantage over conventional robotic systems that they do not require actuators and control. Brachiating, in particular, involves the swinging motion of an animal from one branch to the next. Such systems are usually designed manually by human designers and often are bio-inspired. However, a computational design approach has the capability to search vast design spaces and find solutions that go beyond those possible by manual design. This paper addresses the automated design of passive dynamic systems by introducing a graph grammar-based method that integrates dynamic simulation to evaluate and evolve configurations. In particular, the method is shown to find different, new solutions to the problem of the design of two-dimensional passive, dynamic, continuous contact, brachiating robots. The presented graph grammar rules preserve symmetry among robot topologies. A separation of parametric multi-objective optimization and topologic synthesis is proposed, considering four objectives: number of successful swings, deviation from cyclic motion, required space, and number of bodies. The results show that multiple solutions with varying complexity are found that trade-off cyclic motion and the space required. Compared to research on automated design synthesis of actuated and controlled robotic systems, this paper contributes a new method for passive dynamic systems that integrates dynamic simulation. [ABSTRACT FROM AUTHOR]

This paper presents the modeling and robust low-level control design of a redundant mobile robot with four omnidirectional wheels, the iSense Robotic (iSRob) platform, that was designed to test safe control algorithms. iSRob is a multivariable nonlinear system subject to parameter uncertainties mainly due to friction forces. A multilinear model is proposed to approximate the behavior of the system, and the parameters of these models are estimated from closed-loop experimental data applying Gauss-Newton techniques. A robust control technique, quantitative feedback theory (QFT), is applied to design a proportional-integral (PI) controller for robust low-level control of the iSRob system, being this the main contribution of the paper. The designed controller is implemented, tested, and compared with a gain-scheduling PI-controller based on pole assignment. The experimental results show that robust stability and control effort margins against system uncertainties are satisfied and demonstrate better performance than the other controllers used for comparison. [ABSTRACT FROM AUTHOR]

The disturbances caused by the blood flow and tissue surface motions are major concerns during the motion planning of an intracardiac robotic catheter. Maintaining a stable and safe contact on the desired ablation point is essential for achieving effective lesions during the ablation procedure. In this paper, a probabilistic formulation of the contact stability and the contact safety for intravascular cardiac catheters under the blood flow and surface motion disturbances is presented. Probabilistic contact stability and contact safety metrics, employing a sample-based representation of the blood flow velocity distribution and the heart motion trajectory, are introduced. Finally, the contact stability and safety for an magnetic resonance imaging-actuated robotic catheter under main pulmonary artery blood flow disturbances and left ventricle surface motion disturbances are analyzed in simulation as example scenarios. [ABSTRACT FROM AUTHOR]

This paper presents a novel impedance controller modified with a switching strategy for the purpose of improving safety in human-robot interactions. Under normal operating conditions, an impedance controller is enabled when adequate tracking performance is maintained in the presence of bounded disturbances. However, if disturbances are greater than anticipated such that tracking performance is degraded, the proposed controller temporarily switches modes to a control strategy better apt to limit control inputs. With disturbances returning to the prescribed bounds, tracking performance will be restored and the impedance controller will resume for nominal operation. The control parameters are constrained by a few conditions necessary for smooth operation. First, a pair of equality constraints is required for the control signal to be continuous when switching control modes. Second, a Lyapunov analysis is performed to formulate an equality constraint on the control parameters to ensure only a single switch occurs when changing control modes to avert control chatter. Third, a matrix inequality constraint is necessary to ensure a robust positive invariant set is formed for when impedance control is active. Numerical simulations are provided to illustrate the controller and conditions. The simulation results successfully validate the presented theory, demonstrating how the constraints yield a continuous control signal, eliminate switching chatter, and permit robustness to disturbances. [ABSTRACT FROM AUTHOR]

This paper introduces an adaptive robust trajectory tracking controller design to provably realize stable bipedal robotic walking under parametric and unmodeled uncertainties. Deriving such a controller is challenging mainly because of the highly complex bipedal walking dynamics that are hybrid and involve nonlinear, uncontrolled state-triggered jumps. The main contribution of the study is the synthesis of a continuous-phase adaptive robust tracking control law for hybrid models of bipedal robotic walking by incorporating the construction of multiple Lyapunov functions into the control Lyapunov function. The evolution of the Lyapunov function across the state-triggered jumps is explicitly analyzed to construct sufficient conditions that guide the proposed control design for provably guaranteeing the stability and tracking the performance of the hybrid system in the presence of uncertainties. Simulation results on fully actuated bipedal robotic walking validate the effectiveness of the proposed approach in walking stabilization under uncertainties. [ABSTRACT FROM AUTHOR]

Contact force quality is one of the most critical factors for safe and effective lesion formation during catheter based atrial fibrillation ablation procedures. In this paper, the contact stability and contact safety of a novel magnetic resonance imaging (MRI)-actuated robotic cardiac ablation catheter subject to surface motion disturbances are studied. First, a quasi-static contact force optimization algorithm, which calculates the actuation needed to achieve a desired contact force at an instantaneous tissue surface configuration is introduced. This algorithm is then generalized using a least-squares formulation to optimize the contact stability and safety over a prediction horizon for a given estimated heart motion trajectory. Four contact force control schemes are proposed based on these algorithms. The first proposed force control scheme employs instantaneous heart position feedback. The second control scheme applies a constant actuation level using a quasi-periodic heart motion prediction. The third and the last contact force control schemes employ a generalized adaptive filter-based heart motion prediction, where the former uses the predicted instantaneous position feedback, and the latter is a receding horizon controller. The performance of the proposed control schemes is compared and evaluated in a simulation environment. [ABSTRACT FROM AUTHOR]

The primary goal of this paper is to develop a formal foundation to design nonlinear feedback control algorithms that intrinsically couple legged robots with bio-inspired tails for robust locomotion in the presence of external disturbances. We present a hierarchical control scheme in which a high-level and real-time path planner, based on an event-based model predictive control (MPC), computes the optimal motion of the center of mass (COM) and tail trajectories. The MPC framework is developed for an innovative reduced-order linear inverted pendulum (LIP) model that is augmented with the tail dynamics. At the lower level of the control scheme, a nonlinear controller is implemented through the use of quadratic programming (QP) and virtual constraints to force the full-order dynamical model to track the prescribed optimal trajectories of the COM and tail while maintaining feasible ground reaction forces at the leg ends. The potential of the analytical results is numerically verified on a full-order simulation model of a quadrupedal robot augmented with a tail with a total of 20 degrees-of-freedom. The numerical studies demonstrate that the proposed control scheme coupled with the tail dynamics can significantly reduce the effect of external disturbances during quadrupedal locomotion. [ABSTRACT FROM AUTHOR]

Inspired by human motor control theory, stiffness control is highly effective in manipulation and human-interactive tasks. The implementation of stiffness control in robotic systems, however, has largely been limited to closed-loop control, and suffers from multiple issues such as limited frequency range, potential instability, and lack of contribution to energy efficiency. Variable-stiffness actuator represents a better solution, but the current designs are complex, heavy, and bulky. The approach in this paper seeks to address these issues by using pneumatic actuator as a variable series elastic actuator (VSEA), leveraging the compressibility of the working fluid. In this work, a pneumatic actuator is modeled as an elastic element with controllable stiffness and equilibrium point, both of which are functions of air masses in the two chambers. As such, for the implementation of stiffness control in a robotic system, the desired stiffness! equilibrium point can be converted to the desired chamber air masses, and a predictive pressure control approach is developed to control the timing of valve switching to obtain the desired air mass while minimizing control action. Experimental results showed that the new approach in this paper requires less expensive hardware (on-off valve instead of proportional valve), causes less control action in implementation, and provides good control performance by leveraging the inherent dynamics of the actuator. [ABSTRACT FROM AUTHOR]

This paper develops a tool path optimization method for robotic surface machining by sampling-based motion planning algorithms. In the surface machining process, the tool-tip position needs to strictly follow the tool path curve and the posture of the tool axis should be limited in a certain range. But the industrial robot has at least six degrees-of-freedom (Dof) and has redundant Dofs for surface machining. Therefore, the tool motion of surface machining can be optimized using the redundant Dofs considering the tool path constraints and limits of the tool axis orientation. Due to the complexity of the problem, the sampling-based motion planning method has been chosen to find the solution, which randomly explores the configuration space of the robot and generates a discrete path of valid robot state. During the solving process, the joint space of the robot is chosen as the configuration space of the problem and the constraints for the tool-tip following requirements are in the operation space. Combined with general collision checking, the limited region of the tool axis vector is used to verify the state's validity of the configuration space. In the optimization process, the sum of the path length of each joint of the robot is set as the optimization objective. The algorithm is developed based on the open motion planning library (OMPL), which contains the state-of-the-art sampling-based motion planners. Finally, two examples are used to demonstrate the effiectiveness and optimality of the method. [ABSTRACT FROM AUTHOR]

Time-optimal trajectory planning (TOTP) is a well-studied problem in robotics and manufacturing, which involves the minimization of the time required for the operation point of a mechanism to follow a path, subject to a set of constraints. A TOTP technique, designed for fully specified paths that include abrupt changes in direction, was previously introduced by the first author of this paper: an incremental approach called minimum-time trajectory shaping (MTTS) was used. In the current paper, MTTS is converted to a dynamic technique and adapted for use with cable-driven parallel robots, which exhibit cable tension and motor torque constraints. For many applications, cable tensions along a path are verified after trajectory generation, rather than imposed during trajectory generation. For the technique proposed in this paper, the cable-tension constraints are imposed directly and fully integrated with MTTS, during trajectory generation, thus maintaining a time-optimal solution. MTTS is applied to a test system and path, and compared to the bang-bang technique. With the same constraints, the results obtained with both techniques are found to be very close. However, MTTS can be applied to a wider variety of paths, and accepts constraints on jerk and total acceleration that would be difficult to apply using the bang-bang approach. [ABSTRACT FROM AUTHOR]

Advanced industrial robotic assembly requires the process parameters to be tuned to achieve high efficiency: short assembly cycle (AC) time and high first-time throughput (FTT) rate. This task is usually undertaken offline because of the difficulties in real-time modeling and the lack of efficient algorithms. This paper proposes a support vector regression (SVR)-enabled method to optimize the assembly process parameters without interrupting the normal production process. To reduce the risk of obtaining a local minimum, we consider the trade-off between exploration and exploitation and propose an adaptive optimization process to balance the production processes and the optimization outcome. The proposed methods have been verified using a typical peg-in-hole robotic assembly process, and the results are compared with design of experiment (DOE) methods and genetic algorithm (GA) method in terms of efficiency and accuracy. The experimental results show that our methods are able to maintain the high FTT rate when it drops below 99%, shorten the average AC time by 3.4%, and reduce the number of assembly trials to find the optimized process parameters by 99.6%. [ABSTRACT FROM AUTHOR]

This paper describes the design and control of a robotic elbow system, which is actuated with a novel sleeve muscle actuator. The sleeve muscle is a significant step forward from the traditional pneumatic muscle, and provides a substantially improved performance through a fundamental structural change. Specifically, the sleeve muscle incorporates a cylindrical insert to the center of the pneumatic muscle, which eliminates the central portion of the internal volume. As a result of this change, the sleeve muscle provides multiple advantages over the traditional pneumatic muscle, including the increased force capacity over the entire range of motion, reduced energy consumption, and expedited dynamic response. Furthermore, utilizing the load-bearing tube as the insert, the sleeve muscle enables an innovative "actuation-load bearing" structure, which generates a highly compact robotic system to mimic the structure and functionality of biological limbs. The robotic elbow design in this paper serves an example that shows the design and control process of a robotic joint in this integrated structure. This robotic elbow provides a range of motion of 110deg, approximately 80% of that for a human elbow, and an average torque capacity that exceeds the peak torque of the human elbow. The servo control capability is provided with a model-based sliding-mode control approach, which is able to provide good control performance in the presence of disturbances and model uncertainties. This controller is implemented on the robotic elbow prototype, and the effectiveness was demonstrated with step response and sinusoidal tracking experiments. [ABSTRACT FROM AUTHOR]

This paper presents the main results from a research aiming at the design of an electromechanical actuator for use in the rehabilitation of ankle motor function in patients suffering due to neurological diseases. Motivations for the research project are discussed within the framework of the application of mechatronic concepts for rehabilitation practice. The entire design process is then described, from the definition of project targets through the mechanical concept and control design steps until design validation by means of numerical simulations and tests on a prototype.

This paper applies a robotics-inspired approach to derive a low-dimensional forward-dynamic hybrid model of human walking in the sagittal plane. The low-dimensional model is derived as a subdynamic of a higher-dimensional anthropomorphic hybrid model. The hybrid model is composed of models for single support (SS) and double support (DS), with the transition from SS to DS modeled by a rigid impact to account for the impact at heel-contact. The transition from DS to SS occurs in a continuous manner. Existing gait data are used to specify, via parametrization, the low-dimensional model that is developed. The primary result is a one-degree-of-freedom model that is an exact subdynamic of the higher-dimensional anthropomorphic model and describes the dynamics of walking. The stability properties of the model are evaluated using the method of Poincare. The low-dimensional model is validated using the measured human gait data. The validation demonstrates the observed stability of the measured gait.

This paper presents the design and prototyping of an inherently compliant lightweight hand mechanism. The hand mechanism itself has 15 degrees of freedom and five fingers. Although the degrees of freedom in each finger are coupled, reducing the number of independent degrees of freedom to 5, the 15 degrees of freedom of the hand could potentially be individually actuated. Each joint consists of a novel flexing mechanism that is based on the loading of a compression spring in the axial and transverse direction via a cable and conduit system. Currently, a bench top version of the prototype is being developed; the three joints of each finger are coupled together to simplify the control system. The current control scheme under investigation simulates a control scheme where myoelectric signals in the wrist flexor and extensor muscles are converted in to x and y coordinates on a control scheme chart. Static load-deformation analysis of finger segments is studied based on a 3-dimensional model without taking the stiffener into account, and the experiment validates the simulation.

In this paper we examine a method to control the stepping motion of a paralyzed person suspended over a treadmill using a robot attached to the pelvis. A leg swing motion is created by moving the pelvis without contact with the legs. The problem is formulated as an optimal control problem for an underactuated articulated chain. The optimal control problem is converted into a discrete parameter optimization and an efficient gradient-based algorithm is used to solve it. Motion capture data from an unimpaired human subject is compared to the simulation results from the dynamic motion optimization. Our results suggest that it is feasible to drive repetitive stepping on a treadmill by a paralyzed person by assisting in torso movement alone. The optimized, pelvic motion strategies are comparable to "hip-hiking" gait strategies used by people with lower limb prostheses or hemiparesis. The resulting motions can be found at the web site http://ww.eng.uci.edu/-chwang/project/stepper/stepper.html.

The study of the relationship between the desired system dynamics and the actuation wrench producing those dynamics is important for robotic system analysis. For traditionally actuated robots, the quality indices of dexterity and manipulability quantify this relationship. However, for unilaterally actuated robots (UARs), such as grasping hands and cable-driven parallel robots (CDPRs), these indices cannot be applied due to the unilateral actuation constraint. In this paper, the quality indices of unilateral dexterity (UD) and unilateral maximum force amplification (UMFA) are established for UARs with arbitrary number of actuators. It is shown that these quality indices provide task-independent quantifications of the physical properties of robustness and force amplification for UARs, and they can measure the mechanism's capability both in singular and nonsingular poses. With these indices, manipulability ellipsoid-derived measures can be applied to arbitrary UARs. The significance of the quality indices for robot synthesis and motion generation analysis is illustrated through two case studies: a five-fingered grasp selection problem and the workspace analysis of a spatial CDPR. [ABSTRACT FROM AUTHOR]

In this paper, a new robotic fish propelled by a hybrid tail, which is actuated by two active joints, is developed. The first joint is driven by a servo motor, which generates flapping motions for main propulsion. The second joint is actuated by a soft actuator, an ionic polymer-metal composite (IPMC) artificial muscle, which directs the propelled fluid for steering. A state-space dynamic model is developed to capture the two-dimensional (2D) motion dynamics of the robotic fish. The model fully captures the actuation dynamics of the IPMC soft actuator, two-link tail motion dynamics, and body motion dynamics. Experimental results have shown that the robotic fish is capable of swimming forward (up to 0.45 body length/s) and turning left and right (up to 40deg/s) with a small turning radius (less than half a body length). Finally, the dynamic model has been validated with experimental data, in terms of steady-state forward speed and turning speed at steady-state versus flapping frequency. [ABSTRACT FROM AUTHOR]

This paper proposes a control framework for a cooperative robotic system to grasp and handle an object with known geometry in the presence of uncertainty in robot dynamics. Based on passive decomposition approach, dynamic equations of the cooperative robotic system are decomposed into two decoupled systems, shape and locked systems. The locked system and the shape system are controlled by two fuzzy sliding mode controllers (SMCs). Stability is studied through passivity property and Lyapunov theorem. Simulation results confirm that the proposed control scheme works well. [ABSTRACT FROM AUTHOR]

Bioinspired design of robotic systems can offer many potential advantages in comparison to traditional architectures including improved adaptability, maneuverability, or efficiency. Substantial progress has been made in the design and fabrication of bioinspired systems. While many of these systems are bioinspired at a system architecture level, the design of linkage connections often assumes that motion is well approximated by ideal joints subject to designer-specified box constraints. However, such constraints can allow a robot to achieve unnatural and potentially unstable configurations. In contrast, this paper develops a methodology, which identifies the set of admissible configurations from experimental observations and optimizes a compliant structure around the joint such that motions evolve on or close to the observed configuration set. This approach formulates an analytical-empirical (AE) potential energy field, which "pushes" system trajectories toward the set of observations. Then, the strain energy of a compliant structure is optimized to approximate this energy field. While our approach requires that kinematics of a joint be specified by a designer, the optimized compliant structure enforces constraints on joint motion without requiring an explicit definition of box-constraints. To validate our approach, we construct a single degree-of-freedom elbow joint, which closely matches the AE and optimal potential energy functions and admissible motions remain within the observation set. [ABSTRACT FROM AUTHOR]

This paper describes the design and control of a new chemomuscle actuation system for robotic systems, especially the mobile systems inspired by biological principles. Developed based on the pneumatic artificial muscle, a chemomuscle actuation system features a high power density, as well as similar characteristics to the biological muscles. Furthermore, by introducing monopropellant (a special type of liquid fuel) as the energy storage media, the chemomuscle system leverages the high energy density of liquid fuel and provides a compact form of high-pressure gas supply with a simple structure. The introduction of monopropellant addresses the limitation of pneumatic supply on mobile devices and thus is expected to facilitate the future application of artificial muscle on biorobotic systems. In this paper, the design of a chemomuscle actuation system is presented, as well as a robust controller design that provides effective control for this highly nonlinear system. To demonstrate the proposed chemomuscle actuation system, an experimental prototype is constructed, on which the proposed control algorithm provides good tracking performance. [ABSTRACT FROM AUTHOR]

This paper presents a methodology for design of dissipative assist robots with proven stability during set-point control. A dissipative assist robot is defined as one where the actuators continuously dissipate energy from the robot until the robot reaches the desired set point. We have discussed in this paper that, under well known control laws, it is hard to characterize dissipativity of a general assist robot. However, by appropriately designing the robot through inertia redistribution, the dynamic equations can be modified so that the control laws can now be proven to be both dissipative and stable under set-point control. The proposed method is demonstrated through simulation of a three-link planar manipulator used as an assist robot to modify human functional movements in a vertical plane. [ABSTRACT FROM AUTHOR]

This paper deals with the problem of synthesizing piecewise rational motions of an object that satisfies kinematic constraints imposed by a planar robot arm with revolute joints. This paper brings together the kinematics of planar robot arms and the recently developed freeform rational motions to study the problem of synthesizing constrained rational motions for Cartesian motion planning. Through the use of planar quaternions, it is shown that for the case of a planar 2R arm, the problem of rational motion synthesis can be reduced to that of circular interpolations in two separate planes and that for the case of a planar 3R arm, the problem can be reduced to a combination of circular interpolation in one plane and a constrained spline interpolation in a circular ring on another plane. Due to the limitation of circular interpolation, only C1 continuous rational motions are generated that satisfy the kinematic constraints exactly. For applications that require C2 continuous motions, this paper presents a method for generating C2 continuous motions that approximate the kinematic constraints for planar 2R and 3R robot arms. [ABSTRACT FROM AUTHOR]

This paper presents a concept and implementation of a toolbox for design and application of tripod-based parallel kinematic machines (PKMs). The toolbox is a suite of design tools to support users from conceptual design to actual application of tripod-based PKMs. These design tools have been individually developed in different languages and development environments, and are integrated seamlessly using a JAVA-based platform. Users can access all the design tools through a friendly graphical user interface (GUI). It is the first computer-aided design system specially developed for tripod-based PKMs. The toolbox includes some innovative methodologies, such as a forward kinematics solver, the concept of joint workspace, on-line monitoring based on forward kinematics, and the concept of motion purity. The paper gives an overview on the toolbox architecture and some key technologies. [ABSTRACT FROM AUTHOR]

Singularities form surfaces in the jointspace of a serial manipulator. Pai¨ and Leu (Pai¨ and Leu, 1992, IEEE Trans. Rob. Autom., 8, pp. 545–559) introduced the important notion of generic manipulator, the singularity surfaces of which are smooth and do not intersect with each other. Burdick (Burdick, 1995, J. Mech. Mach. Theor., 30, pp. 71–89) proposed a homotopy-based classification method for generic 3R manipulators. Through this classification method, it was stated in Wenger, 1998, J. Mech. Des., 120, pp. 327–332 that there exist exactly eight classes of generic 3R manipulators. A counterexample to this classification is provided: a generic 3R manipulator belonging to none of the eight classes identified in (Wenger, 1998, J. Mech. Des., 120, pp. 327–332) is presented. The weak point of the proof given in (J. Mech. Des., 120, pp. 327–332) is highlighted. The counterexample proves the existence of at least nine homotopy classes of generic 3R manipulators. The paper points out two peculiar properties of the manipulator proposed as a counterexample, which are not featured by any manipulator belonging to the eight homotopy classes so far discovered. Eventually, it is proven in this paper that at most four branches of the singularity curve can coexist in the jointspace of a generic 3R manipulator and therefore at most eleven homotopy classes are possible. [ABSTRACT FROM AUTHOR]

This paper addresses the robot path planning problem in our effort to develop a fully automated dimensional measurement system using an eye-in-hand robotic manipulator. First, the CAD-based vision sensor planning system developed in our lab is briefly introduced; it uses both the CAD model and the camera model to plan camera viewpoints. The planning system employs a decomposition-based approach to generate camera viewpoints that satisfy given task constraints. Second, to improve the efficiency of the eye-in-hand robot inspection system, robot path planning is studied, which is the focus of this paper. This problem is rendered as a Traveling Salesman Problem (TSP). A new hierarchical approach is developed to solve the TSP into its suboptimality. Instead of solving a large size TSP, this approach utilizes the clustering nature of the viewpoints and converts the TSP into a clustered Traveling Salesman Problem (CTSP). A new algorithm, which favors the intergroup paths, is proposed to solve the CTSP quickly. Performance of the new algorithm is analyzed. It is shown that instead of a fixed performance ratio as reported in some existing work, a constant bound can be achieved which is related to the diameter of the clusters. Experimental results demonstrate the effectiveness of the robot motion planning system. The proposed path planning approach can obtain sub-optimal solutions quickly for many large scale TSPs, which are common problems in many robotic applications. [ABSTRACT FROM AUTHOR]

This paper presents a framework to build hybrid cells that support safe and efficient human-robot collaboration during assembly operations. Our approach allows asynchronous collaborations between human and robot. The human retrieves parts from a bin and places them in the robot's workspace, while the robot picks up the placed parts and assembles them into the product. We present the design details of the overall framework comprising three modules--plan generation, system state monitoring, and contingency handling. We describe system state monitoring and present a characterization of the part tracking algorithm. We report results from human-robot collaboration experiments using a KUKA robot and a three-dimensional (3D)-printed mockup of a simplified jet-engine assembly to illustrate our approach. [ABSTRACT FROM AUTHOR]

This paper presents the development of a robotic finger driven by nonconventional actuators, consisting of thin shape memory alloy (SMA) wires. In order to monitor and control the angles formed by each phalanx, a specific system for capturing and interpreting digital images was implemented. By image processing, this system is capable to determine the angles without the need for installation of phalanx rotation sensors, leading to weight and volume reduction of the prototype. For this artificial vision system, a simple camera with a fuzzy logic control technique was used, which was very effective in monitoring the position of the robotic finger. [ABSTRACT FROM AUTHOR]