Detecting the Distribution of a Robotic Swarm in Uncertain Conditions
Eliashiv Cohen, Yakov Idelson, Oded Median, Nir Shvalb, Shlomi Hacohen · 2019
Localization problem of a swarm is required for most tasks related to swarms. In many cases real world sensors possess inherent measurement error. Nevertheless, having a large set of inter-measurements may compensate for this. The paper implements Extended Kalman Filter to estimate the swarm's distribution. Indeed, a set of simulated experiments demonstrate the algorithm robustness and simplicity. Finally, we show that the resulting error estimation is reliable.