An Intention Guided Hierarchical Framework for Trajectory-based Teleoperation of Mobile Robots

Abstract

In human-in-the-loop navigation, the operator’s intention is to locally avoid obstacles while planning long-horizon paths in order to complete the navigation task. We propose a hierarchical teleoperation framework that captures these characteristics of intention, and generates trajectories that are locally safe and follow the operator’s global plan. The hierarchical teleoperation framework consists of 1) a global path which encapsulates the intended direction of the operator, 2) local trajectories that circumvent obstacles near the vehicle’s vicinity while following the global path, and 3) safety monitoring to avoid possible imminent collisions. By removing the operator from providing dynamic-level control inputs and instead having inputs inform trajectory generation, we show a significant reduction of the operator’s engagement while maintaining smooth performance.We showcase hierarchical teleoperation in navigation tasks in a random forest environment and a high-clutter warehouse characterized by narrow gaps and dense obstacles. With our method, we maintain consistent high speed throughout the task with smooth jerk profiles, decreased time to completion, and significantly reduced operator engagement.