Igor Gaponov

This paper discusses how to develop and implement a bimanual teleoperation system using an exoskeleton suit and two collaborative robots. In the mathematical model, two methods of mapping have been implemented: Joint space mapping via direct control and Cartesian space mapping using Saturation in the Null Space. Both methods are verified in simulation using the developed mathematical model and on hardware using KUKA IIWA robots. A pick-and-place experiment is designed, and the corresponding end-effector positions of the master and the slave devices are obtained. Force feedback is introduced using two methods to improve accuracy and to show the applicability not only for collaborative robots but also on industrial manipulators.

Adaptive control and parameter estimation have been widely employed in robotics to deal with parametric uncertainty. However, these techniques may suffer from parameter drift, dependence on acceleration estimates and conservative requirements for system excitation. To overcome these limitations, composite adaptation laws can be used. In this paper, we propose an enhanced composite adaptive control approach for robotic systems that exploits the accelerationfree momentum dynamics and regressor extensions to offer faster parameter and tracking convergence while relaxing excitation conditions and providing a clear physical interpretation. The effectiveness of the proposed approach is validated through experimental evaluation on a 3-DoF robotic leg.