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Soft robotics has opened a unique path to flexibility and environmental adaptability, learning from nature and reproducing biological behaviors. Nature implies answers for how to apply robots to real life. To find out how we learn from creatures to design and apply soft robots, in this Review, we propose a classification method to summarize soft robots based on different functions of biological systems: self-growing, self-healing, self-responsive, and self-circulatory. The bio-function based classification logic is presented to explain why we learn from creatures. State-of-art technologies, characteristics, pros, cons, challenges, and potential applications of these categories are analyzed to illustrate what we learned from creatures. By intersecting these categories, the existing and potential bio-inspired applications are overviewed and outlooked to finally find the answer, that is, how we learn from creatures. [ABSTRACT FROM AUTHOR]

Prostate biopsy procedures as a gold standard for early screening of prostate cancer often suffer from multipass needle perforations to irrelevant perineal tissue, high complication risk, and time consumption. To address these challenges, this article proposes a transurethral prostate biopsy robot that can deliver a flexible biopsy needle inside the prostate from different angles and thus obtain tissue samples from multiple locations. Emphasis is on the design and validation of the transurethral prostate biopsy robot with a detailed introduction of the working principle, mechanism modeling, and function testing. Phantom experiments in kiwi fruit puncture experiments and prostate phantom puncture experiments have demonstrated their potential in clinical application. The transurethral biopsy robot features a 7-mm tubular dual-roller bending mechanism together with a compact driver mechanism. The flexible biopsy needle can bend from 16.0 $^\circ$ to 55.8 $^\circ$ with a translational stroke of 32.5 mm and an overall rotational stroke of 360 $^\circ$ , which enable coverage a volume of 142.2 mL, more extensive than that of an enlarged prostate. The average angle positioning and overall positioning error are 0.82 $^{\circ }$ and 1.2 mm, respectively. It can provide a minimum of 6.3-N puncture force. The proposed transurethral prostate biopsy procedure is a unique inside-out robotic prostate biopsy method, contributing to a safer and less invasive prostate biopsy procedure. [ABSTRACT FROM AUTHOR]

The development and use of soft or flexible structural matters across various research domains have drastically increased in recent decades. Its flexible, compliant nature and interactive safety have made it a preferred candidate compared to its rigid bodied counterparts. However, the lack of robust soft robot detection and localization techniques has constrained its feedback control system, limiting its application. This paper proposes a novel depth sensor-based detection and tracking algorithm adaptive to shape morphing robots. The detection algorithm first employs optimal iterative threshold segmentation on the depth image to remove background and detect occlusions. Blob detection and polygon approximation using Fourier descriptor techniques are then utilized to detect and extract the contours of the shape morphing soft robots. Finally, using the pixel coordinates obtained from the detection algorithm, transformation is applied from the pixel coordinate system to the world coordinate system on the depth image to achieve motion tracking in 3D space. Qualitative and quantitative assessments prove that the detection algorithm is robust and accurate in tracking shape morphing soft robots. [ABSTRACT FROM AUTHOR]

This article presents a robotic needle positioning approach with a novel 4-DoF parallel positioner, two back-driveable 2-channel linear/rotational driver, and a machine–body interface. Being more compact and flexible, Ni–Ti alloy wire-based Bowden cable transmission is introduced to connect the positioner and the drivers. For this new mechanism, forward and inverse kinematics are derived, and the workspace is analyzed. The mechanism’s maximum incidence angle is 45 $^{\circ }$ , and the stroke of the slider is 41 mm. The structural size of one positioner is $\varnothing$ 70 mm × 45 mm. The compact size and lightweight of the positioner make it readily mountable on the skull or attached to other parts of the body. We fabricated a 3D printed proof-of-concept prototype of the system and tested its performance. The open-loop positioning accuracy of the slider and rotor is within $\pm$ 1 mm and from $-0.8^{\circ }$ to 1.5 $^{\circ }$ , respectively. The trajectory tracking error of the system is within 1.71 mm. The stiffness of the positioner in the x- and y-directions can be calculated as 9.03 and 11.91 N/mm, respectively. Finally, an image-guided navigation framework based on electromagnetic tracking demonstrates the feasibility of the proposed system on a phantom study. [ABSTRACT FROM AUTHOR]

This paper introduces a systematical interval-based framework of inherent uncertainties and pose evaluation for a class of soft continuum robots driven by flexible shafts. A more general model of continuum robots driven by shaft tendons is extended from prior kinematic models. On top of the proposed model, the interval-based analysis is presented to analyze and characterize the pose of continuum robots considering uncertainties in kinematic parameters and joint inputs. A 3-D printed bending actuator driven by a flexible shaft is evaluated for case study based on the proposed interval-valued framework. This paper investigates and compares a couple of refinement methods and proposes a new way of sensitivity analysis of model parameters based on interval arithmetic. The kinematic and mechanics parameters are measured and identified experimentally with a representation of intervals. The in-plane motion experiment validates that the computed bounds can enclose all the measured tip positions with consideration of the measurement uncertainty. The method is also validated when external loading is exerted. Note to Practitioners—With the fast development of soft robotics, the increasing number of soft robotic manipulators show great potentials of application in industries such as agriculture, biomedicine, home automation, manufacturing, logistics, and domestic service. Thanks to the mechanical compliance, soft manipulators demonstrate environmental adaptability at the cost of very precise positioning. However, the guaranteed bounds of the reaching range are valuable in order to provide users a good knowledge of the product performance, which is the motivation of this paper. This paper provides not only a method and framework based on interval analysis to evaluate the pose of soft actuators, but also a case study of uncertainty interval characterization procedure which is domain-specific for soft actuators. The presented method framework can be implemented for continuum manipulators and soft actuators as well as any other robotic devices featured by such flexible components. [ABSTRACT FROM AUTHOR]

Accurate high-temperature measurement is very important for process monitoring of an industrial system. Infrared thermometers usually can handle no more than 1000 °C and should use some expensive accessories for higher temperature measurements. This paper proposes a low-cost pyrometry system with nonlinear multisense partial least squares (NMSPLS). The ordinary camera with different filters is designed to collect the images of hot object at different wavelengths, and the NMSPLS is presented for predicting the temperature of the hot object from the obtained images. For the proposed method, the obtained images are represented by the multisense tensor, where red, green, and blue are regarded as three different dimensions in a sense of the tensor, respectively. The proposed method integrates an outer model and a nonlinear inner model. For the outer model, the independent variables and the dependent variables are projected into a low-dimensional common latent subspace. The weight matrices are calculated from the independent variables by the tucker decomposition, and the single value decomposition is adopted for extracting the latent variables (Lvs) based on the covariance between the independent variables and the dependent variables. For the nonlinear inner model, the neural network is adopted and the extracted Lvs are used as the input and the output of the neural network, respectively. Two real experiments are performed for estimating the proposed method. The experimental results verify that the proposed method can be applied for pyrometry and have higher effectiveness. [ABSTRACT FROM AUTHOR]

Data-defect would affect the data quality and the analysis results of data mining. This paper presents a data-defect inspection method with kernel-neighbor-density-change outlier factor (KNDCOF). The definition of kernel neighbor density is proposed to represent the density of each object in database, and the ascending distance series (ADS) of each object is calculated based on the kernel distance between the object and its neighbors. Then, the average density fluctuation (ADF) of the object is established according to the weighted sum of the square of density difference between the object and others in ADS. Finally, the KNDCOF of the object is equal to the ratios of the ADF of the object and the average ADF of neighbors of the object. The degree of the object being an outlier is indicated by the KNDCOF value. The experiments are performed on three real data sets to evaluate the effectiveness of the proposed method. The experimental results verify that the proposed method has higher quality of data-defect inspection and does not increase the time complexity.

Note to Practitioners–Data-defect inspection is an important procedure of data preprocessing for a real industrial process. This paper presents a data-defect inspection method with kernel-neighbor-density-change outlier factor to identify the outliers, and addresses the challenges associated with the strong correlation and the nonlinearity of the industrial data. The proposed method calculates the outlier factor for each object, which quantifies how outlying it is. The outlier factor is based on the density difference between the object and its neighbors. The larger the outlier factor of an object is, the higher the outlierness of the object is. The proposed method could be wildly used in an industrial complex data set with different density regions. In the industrial field, engineers can deal with the objects with high outlier factor values based on the actual requirements. [ABSTRACT FROM AUTHOR]

Multirobot comanipulation shows great potential in surpassing the limitations of single-robot manipulation in complicated tasks such as robotic surgeries. However, a dynamic multirobot setup in unstructured environments poses great uncertainties in robot configurations. Therefore, the coordination relationships between the end-effectors and other devices, such as cameras (hand–eye calibration) and tools (tool–flange calibration), as well as the relationships among the base frames (robot–robot calibration) have to be determined timely to enable accurate robotic cooperation for the constantly changing configuration of the systems. We formulated the problem of hand–eye, tool–flange, and robot–robot calibration to a matrix equation \mathbfAXB=YCZ. A series of generic geometric properties and lemmas were presented, leading to the derivation of the final simultaneous algorithm. In addition to the accurate iterative solution, a closed-form solution was also introduced based on quaternions to give an initial value. To show the feasibility and superiority of the simultaneous method, two nonsimultaneous methods were compared through thorough simulations under various robot movements and noise levels. Comprehensive experiments on real robots were also performed to further validate the proposed methods. The comparison results from both simulations and experiments demonstrated the superior accuracy and efficiency of the proposed simultaneous calibration method. [ABSTRACT FROM PUBLISHER]

We propose an efficient and effective magnetic tracking method in this paper. The tracking method is based on tri-axial transmitting coils and uniaxial sensing of the generated electromagnetic field. Three mutually orthogonal transmitting coils are excited simultaneously with alternating current (AC) signals of different frequency. At a specific position, the sum of amplitude square of the three different frequency sensing signals will reach maximum when the uniaxial coil points to the tri-axial transmitting coils. The maximum value is reciprocally proportional to the cube of the distance between the transmitter and receiver. By processing the output signals from the uniaxial sensing coil when it is rotating, the direction and distance between the sensing coil and transmitting coils can be decided with an efficient method with low calculation overheads. Experiments were conducted to validate the proposed method. [ABSTRACT FROM PUBLISHER]