Infrastructure-free Localization of Aerial Robots with Ultrawideband Sensors
This addresses the need for reliable and versatile localization in multi-robot systems operating in occluded or infrastructure-limited environments, representing an incremental improvement over existing methods.
The authors tackled the problem of enabling aerial robots in a swarm to localize each other without relying on external infrastructure like motion capture or GPS, by proposing an on-board framework using ultrawideband sensors, which achieved highly accurate estimates for various speed profiles in simulations and experiments.
Robots in a swarm take advantage of a motion capture system or GPS sensors to obtain their global position. However, motion capture systems are environment-dependent and GPS sensors are not reliable in occluded environments. For a reliable and versatile operation in a swarm, robots must sense each other and interact locally. Motivated by this requirement, here we propose an on-board localization framework for multi-robot systems. Our framework consists of an anchor robot with three ultrawideband (UWB) sensors and a tag robot with a single UWB sensor. The anchor robot utilizes the three UWB sensors as a localization infrastructure and estimates the tag robot's location by using its on-board sensing and computational capabilities solely, without explicit inter-robot communication. We utilize a dual Monte-Carlo localization approach to capture the agile maneuvers of the tag robot with an acceptable precision. We validate the effectiveness of our algorithm with simulations and indoor and outdoor experiments on a two-drone setup. The proposed dual MCL algorithm yields highly accurate estimates for various speed profiles of the tag robot and demonstrates a superior performance over the standard particle filter and the extended Kalman Filter.