Reactive Temporal Logic-based Planning and Control for Interactive Robotic Tasks

TL;DR

This paper presents a modular control architecture combining temporal logic and dynamical systems to enable safe, reactive, and adaptive robot interaction with humans, ensuring formal safety guarantees while maintaining flexibility.

Contribution

It introduces a reactive temporal logic framework integrated with continuous control methods for adaptive, safe human-robot interaction tasks.

Findings

Successfully demonstrated on Franka robot arm performing wiping tasks.

Achieved safe and reactive motion planning with formal guarantees.

Adapted to environmental changes and human interactions.

Abstract

Robots interacting with humans must be safe, reactive and adapt online to unforeseen environmental and task changes. Achieving these requirements concurrently is a challenge as interactive planners lack formal safety guarantees, while safe motion planners lack flexibility to adapt. To tackle this, we propose a modular control architecture that generates both safe and reactive motion plans for human-robot interaction by integrating temporal logic-based discrete task level plans with continuous Dynamical System (DS)-based motion plans. We formulate a reactive temporal logic formula that enables users to define task specifications through structured language, and propose a planning algorithm at the task level that generates a sequence of desired robot behaviors while being adaptive to environmental changes. At the motion level, we incorporate control Lyapunov functions and control barrier functions to compute stable and safe continuous motion plans for two types of robot behaviors: (i) complex, possibly periodic motions given by autonomous DS and (ii) time-critical tasks specified by Signal Temporal Logic~(STL). Our methodology is demonstrated on the Franka robot arm performing wiping tasks on a whiteboard and a mannequin that is compliant to human interactions and adaptive to environmental changes.