A Robust Antenna Provides Tactile Feedback in a Multi-legged Robot

TL;DR

This paper introduces a tactile antenna system for multi-legged robots that improves navigation in complex, confined environments by providing real-time contact sensing and enabling autonomous maneuvering without relying on vision.

Contribution

The study presents a biologically inspired tactile antenna design with gradient compliance, integrated into a control system for improved obstacle detection and navigation in complex terrains.

Findings

A relationship between antenna curvature and contact force was established.

The tactile feedback system enabled reliable obstacle avoidance and recovery.

Robots successfully navigated obstacle-rich and confined environments using the new sensing method.

Abstract

Multi-legged elongate robots hold promise for maneuvering through complex environments. Prior work has demonstrated that reliable locomotion can be achieved using open-loop body undulation and foot placement on rugose terrain. However, robust navigation through confined spaces remains challenging when body-environment contact is extensive and terrain rheology varies rapidly. To address this challenge, we develop a pair of tactile antennae for multi-legged robots that enable real-time sensing of surrounding geometry, modeling the morphology and function of biological centipede antennae. Each antenna features gradient compliance, with a stiff base and soft tip, allowing repeated deformation and elastic recovery. Robophysical experiments reveal a relationship between continuous antenna curvature and contact force, leading to a simplified mapping from antenna deformation to inferred discrete collision states. We incorporate this mapping into a controller that selects among a set of locomotor maneuvers based on the inferred collision state. Experiments in obstacle-rich and confined environments demonstrate that tactile feedback enables reliable steering and allows the robot to recover from near-stuck conditions without requiring global environmental information or real-time vision. These results highlight how mechanically tuned tactile appendages can simplify sensing and enhance autonomy in elongate multi-legged robots operating in constrained spaces.