Design and Control of a Series–Parallel Elastic Actuator for a Weight-Bearing Exoskeleton Robot

Weight-bearing exoskeletons are robots that need to carry loads and interact with humans frequently. Therefore, the actuators of these exoskeletons are supposed to be capable of outputting sufficient force with high compliance and little weight. A series–parallel elastic actuator (SPEA) is designed, in this work, to meet the demanding requirements of an exoskeleton robot called PALExo. A gas spring is installed in parallel with an electric cylinder to adjust the force output range of the actuator according to the needs of the exoskeleton. A series elastic module (SEM) is installed in series with the electric cylinder and gas spring to improve the compliance of the actuator, the stiffness of which is variable to adapt to the different stiffness requirements of the exoskeleton’s legs in the standing phase and swinging phase. A force controller combining dynamic compensation and a cascade control with an inner velocity loop and a disturbance observer is designed for the SPEA. The performance of the force controller is verified by experiments and the results demonstrate that the controller has good adaptability to the stiffness of the SEM.

Control of a Robotic Flexible Endoscope Holder for Laparoscopic Surgery

In this paper, we present an integrated robotic arm with a flexible endoscope for laparoscopy. The endoscope holder is built to mimic a human operator that reacts to the surgeon's push while maintaining both the incision opening through the patient's body and the center of the endoscopic image. An impedance control algorithm is used to react to the surgeon's push when the robotic arm gets in the way. A modified software remote center-of-motion (RCM) constraint formulation then enables simultaneous RCM and impedance control. We derived the kinematic relationship between the robotic arm and line of sight of the flexible endoscope for image center control. Using this kinematic model, we integrated the task control for RCM and surgeon cooperation and the endoscope image centering into a semi-autonomous system. Implementation of the control algorithm with both matlab simulation and the HIWIN RA605-710 robotic arm with a MitCorp F500 flexible endoscope demonstrated the feasibility of the proposed algorithm.

A Novel Coordinated Motion Fusion-Based Walking-Aid Robot System

Human locomotion is a coordinated motion between the upper and lower limbs, which should be considered in terms of both the user’s normal walking state and abnormal walking state for a walking-aid robot system. Therefore, a novel coordinated motion fusion-based walking-aid robot system was proposed. To develop the accurate human motion intention (HMI) of such robots when the user is in normal walking state, force-sensing resistor (FSR) sensors and a laser range finder (LRF) are used to detect the two HMIs expressed by the user’s upper and lower limbs. Then, a fuzzy logic control (FLC)-Kalman filter (LF)-based coordinated motion fusion algorithm is proposed to synthesize these two segmental HMIs to obtain an accurate HMI. A support vector machine (SVM)-based fall detection algorithm is used to detect whether the user is going to fall and to distinguish the user’s falling mode when he/she is in an abnormal walking state. The experimental results verify the effectiveness of the proposed algorithms.

Compliance Control and Human–Robot Interaction: Part 1 — Survey

Compliance control is highly relevant to human safety in human–robot interaction (HRI). This paper presents a review of various compliance control techniques. The paper is aimed to provide a good background knowledge for new researchers and highlight the current hot issues in compliance control research. Active compliance, passive compliance, adaptive and reinforcement learning-based compliance control techniques are discussed. This paper provides a comprehensive literature survey of compliance control keeping in view physical human robot interaction (pHRI) e.g., passing an object, such as a cup, between a human and a robot. Compliance control may eventually provide an immediate and effective layer of safety by avoiding pushing, pulling or clamping in pHRI. Emerging areas such as soft robotics, which exploit the deformability of biomaterial as well as hybrid approaches which combine active and passive compliance are also highlighted.

A robust static decoupling algorithm for 3-axis force sensors based on coupling error model and ε-SVR

Coupling errors are major threats to the accuracy of 3-axis force sensors. Design of decoupling algorithms is a challenging topic due to the uncertainty of coupling errors. The conventional nonlinear decoupling algorithms by a standard Neural Network (NN) are sometimes unstable due to overfitting. In order to avoid overfitting and minimize the negative effect of random noises and gross errors in calibration data, we propose a novel nonlinear static decoupling algorithm based on the establishment of a coupling error model. Instead of regarding the whole system as a black box in conventional algorithm, the coupling error model is designed by the principle of coupling errors, in which the nonlinear relationships between forces and coupling errors in each dimension are calculated separately. Six separate Support Vector Regressions (SVRs) are employed for their ability to perform adaptive, nonlinear data fitting. The decoupling performance of the proposed algorithm is compared with the conventional method by utilizing obtained data from the static calibration experiment of a 3-axis force sensor. Experimental results show that the proposed decoupling algorithm gives more robust performance with high efficiency and decoupling accuracy, and can thus be potentially applied to the decoupling application of 3-axis force sensors.

Automatic Generation of High-level Contact State Space between 3D Curved Objects

Information of high-level, topological contact states is useful and sometimes even necessary for a wide range of applications, from robotic tasks involving compliant motion to virtual prototyping and simulation. This paper addresses how to represent concisely and generate automatically graphs of contact states between 3D curved objects of a broad class, which may include smooth curved or planar surfaces. The approach is sound and complete if the step size of discretization is smaller than a finite threshold. By exploiting topological and geometrical constraints, it is also quite efficient. The implemented examples demonstrate the effectiveness of the approach.

A New Method of Force Control for Unknown Environments

Current robotic systems are expected to interact with unknown environment where controlling the interaction forces becomes an important issue. We propose a new control technique for force control on unknown environments that tunes the force controller based on online estimation of the environment parameters. However, the proposed approach overcomes the need for precise estimation of environment parameters, which are needed in many system identification-based force control approaches. This framework uses an artificial neural network (ANN)-based proportional-integral (PI)-gain scheduling force controller to track the desired force by adjusting control gains such that error in parameter estimation can be accommodated. Experimental results are presented to demonstrate the efficacy of the proposed control framework. Finally, the advantages and limitations of the proposed controller are discussed.