Ultra-Wideband Teach and Repeat

TL;DR

This paper introduces an ultra-wideband (UWB) ranging-based Teach and Repeat system enabling robots to autonomously retrace paths with high accuracy in indoor environments, suitable for resource-constrained vehicles.

Contribution

It presents a novel UWB ranging protocol and T&R algorithm that achieve reliable indoor path retracing using minimal onboard resources.

Findings

Successful trajectory retracing with sub-meter accuracy in simulation.

Effective fusion of UWB, IMU, and height data for mapping.

Validation of the approach in simulated environments.

Abstract

Autonomously retracing a manually-taught path is desirable for many applications, and Teach and Repeat (T&R) algorithms present an approach that is suitable for long-range autonomy. In this paper, ultra-wideband (UWB) ranging-based T&R is proposed for vehicles with limited resources. By fixing single UWB transceivers at far-apart unknown locations in an indoor environment, a robot with 3 UWB transceivers builds a locally consistent map during the teach pass by fusing the range measurements under a custom ranging protocol with an on-board IMU and height measurements. The robot then uses information from the teach pass to retrace the same trajectory autonomously. The proposed ranging protocol and T&R algorithm are validated in simulation, where it is shown that the robot can successfully retrace the taught trajectory with sub-metre tracking error.