This paper proposes a robot following method to follow the sewing action of human upper limbs. The purpose of this paper is to demonstrate that robots can assist workers in the future. Compared with the visual servo method, the accuracy is much improved.

In this paper, a gait analysis algorithm for a lower limb rehabilitation robot is proposed. The algorithm realizes the division of gait temporal information and the design of a gait spatiotemporal parameter algorithm based on lidar. A spatial parameter-splicing algorithm based on a time series is proposed, which effectively reduces the influence of errors on gait parameters. Based on the gait algorithm, aiming at real-time algorithm performance, a dynamic window method is proposed.

Traditional path-planning algorithms for bending robots are often a sequence of multiple line segments and an unsmoothed curve, which causes a discontinuous robot motion. A smooth path can ensure continuous motion. We propose an improved artificial potential field-based path-planning method based on the idea of a rapidly exploring random tree (RRT) algorithm, reducing the length of and smoothing the path, thus solving the path-planning problem of a multi-degrees-of-freedom (DOF) bending robot.

Robot-assisted rehabilitation has proven to be effective for improving the motor performance of patients with neuromuscular injuries. Therefore, the main purpose of this paper is to present a new patient-cooperative control framework for an end-effector upper-limb rehabilitation robot that provides robot-assisted training for individuals with neuromuscular disorders. The feasibility of the proposed control scheme is validated via training experiments using five healthy subjects.

We introduce different test scenarios and set-ups for a force control assessment. The force control of Universal Robots (UR10e) and FerRobotics (ACF-K 109/04) are evaluated. A force/torque sensor, mounted below a work piece, measures the applied force by the UR or by the ACF. Results for both UR and ACF force control are presented for varying desired contact velocities and forces. These results show the advantage of the ACF-K 109/04 over the UR10e force control for highly dynamic scenarios.