Unfreezing Social Navigation: Dynamical Systems based Compliance for Contact Control in Robot Navigation

TL;DR

This paper introduces a dynamical systems-based control approach for mobile robots that ensures safe contact handling and obstacle avoidance, enabling robots to react instantaneously to contact and pedestrian presence in crowded environments.

Contribution

It presents a novel force-limited, obstacle avoidance controller integrated into a dynamical system for real-time contact mitigation in robot navigation.

Findings

Robot can handle contact forces up to 9 N at speeds under 1 m/s.

The controller enables safe obstacle avoidance without additional collisions.

Active compliance improves safety during unintended contact.

Abstract

Large efforts have focused on ensuring that the controllers for mobile service robots follow proxemics and other social rules to ensure both safe and socially acceptable distance to pedestrians. Nonetheless, involuntary contact may be unavoidable when the robot travels in crowded areas or when encountering adversarial pedestrians. Freezing the robot in response to contact might be detrimental to bystanders' safety and prevents it from achieving its task. Unavoidable contacts must hence be controlled to ensure the safe and smooth travelling of robots in pedestrian alleys. We present a force-limited and obstacle avoidance controller integrated into a time-invariant dynamical system (DS) in a closed-loop force controller that let the robot react instantaneously to contact or to the sudden appearance of pedestrians. Mitigating the risk of collision is done by modulating the velocity commands upon detecting a contact and by absorbing part of the contact force through active compliant control when the robot bumps inadvertently against a pedestrian. We evaluated our method with a personal mobility robot -- Qolo -- showing contact mitigation with passive and active compliance. We showed the robot able to overcome an adversarial pedestrian within 9 N of the set limit contact force for speeds under 1 m/s. Moreover, we evaluated integrated obstacle avoidance proving the ability to advance without incurring any other collision.