The PAM robot arm is belonged to highly nonlinear systems where perfect knowledge of their parameters is unattainable by conventional modeling techniques because of the timevarying inertia, hysteresis and other joint friction model uncertainties. To guarantee a good tracking performance, robust-adaptive control approaches combining conventional methods with new learning techniques are required....

Learning optimal control policies directly on physical systems is challenging. Even a single failure can lead to costly hardware damage. Most existing model-free learning methods that guarantee safety, i.e., no failures, during exploration are limited local optima. This work proposes GoSafeOpt as the first provably safe and algorithm safely discover globally for with high-dimensional state spac...

Effective teleoperation of the small-scale and highly-integrated robots for single-port surgery (SPS) imposes unique control human-robot interaction challenges. Traditional isometric schemes mainly focus on end-to-end trajectory mapping, which is problematic when applied to SPS robotic control, especially dual-arm coordinated operation. Inspired by human arm configuration in boxing maneuvers, a...

Dual-arm robotic system for load transportation in hazardous environments is considered in this study. First, physical model of the robot arms with the load is presented and related equations of motion are obtained. Friction forces arising on the contact points between the load and robot arm tips are also taken into account. Then, robust non-chattering sliding mode control is used in order to o...