Safe Trajectory Tracking for Robotic Manipulator with Prescribed Performance in Confined Spaces

This paper addresses the issue of safe trajectory tracking for robotic manipulators operating in confined spaces that often exhibit asymmetric geometric structures, such as narrow passages or cluttered obstacle fields. We introduce an innovative model-free control strategy aimed at guaranteeing safe trajectory tracking by constraining joint trajectory tracking errors within prescribed safe bounds. To achieve the desired tracking objective, an error transformation mechanism is developed. Notably, the robustness of this mechanism against model uncertainties eliminates the necessity for knowledge of the system model, enabling model-free control. Additionally, we introduce a Monte Carlo-based search strategy that integrates motion planning, which provides a collision-free feasible reference trajectory, with control, which ensures runtime safety. This framework operates autonomously and guarantees safety at both the planning and control layers. The controller’s robustness, along with its autonomous implementation from planning to control, facilitates practical deployment in complex real-world environments and is effectively validated on a Baxter robotic platform.