Ultra-Wideband Teach and Repeat
This addresses indoor navigation for robots with limited resources, but it is incremental as it builds on existing Teach and Repeat methods with UWB enhancements.
The paper tackled autonomous path retracing for resource-limited vehicles by proposing an ultra-wideband (UWB) ranging-based Teach and Repeat algorithm, achieving sub-metre tracking error in simulation.
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.