Peer-to-Peer Relative Localization of Aerial Robots With Ultrawideband Sensors

Robots in swarms take advantage of localization infrastructure, such as a motion capture system or global positioning (GPS) sensors to obtain their position, which can then be communicated other robots for swarm coordination. However, the availability infrastructure needs not guaranteed, e.g., GPS-denied environments. Likewise, communication overhead associated with broadcasting locations may undesirable. For reliable and versatile operation swarm, must sense each interact locally. Motivated by this requirement, we propose an onboard relative framework multirobot systems. The setup consists anchor robot three ultrawideband (UWB) tag single UWB sensor. utilizes estimate robot’s location using its sensing computational capabilities solely, without explicit interrobot communication. Because lack physical separation that is typical fixed systems, introduce filtering methods improve estimation tag’s location. In particular, utilize mixture Monte Carlo (MCL) approach maneuvers acceptable precision. We validate effectiveness our algorithm simulations well indoor outdoor field experiments on two-drone setup. proposed MCL yields highly accurate estimates various speed profiles demonstrates superior performance over standard particle filter extended Kalman filter.