Feasibility-aware Hybrid Control for Motion Planning under Signal Temporal Logics

TL;DR

This paper introduces a hybrid control method for motion planning that unifies planning and control, using feasibility analysis and barrier functions to handle complex tasks and avoid deadlocks.

Contribution

It presents a novel hybrid modeling approach with feasibility analysis and barrier functions for improved motion planning under complex constraints.

Findings

Effective handling of multiple overlapping spatio-temporal tasks

Successful avoidance of deadlocks in complex robotic workspaces

Robustness to input saturation demonstrated in simulations

Abstract

In this work, a novel method for planar task and motion planning based on hybrid modeling is proposed. By virtue of a discrete variable which models local constraint satisfaction and enables local feasibility analysis, the proposed control architecture unifies planning with control design. Concurrently, control barrier functions are designed on a transformed disk version of the original nonconvex and geometrically complex robotic workspace, thus amending the issue of deadlocks. Simulations of the proposed method indicate effective handling of multiple overlapping spatio-temporal tasks even in the face of input saturation.