Relative Localization in Multi Robot Systems Based on Dead Reckoning and UWB Ranging
Combining dead reckoning and Ultra Wideband (UWB) ranging information to achieve relative localization (RL) becomes prevalent in recent years. However, two main problems, i.e. pose initialization and distributed implementation, are rarely investigated in practical multi robot systems. In this paper, a novel two stage RL method is proposed to fill this gap, wherein an initialization strategy, using robot to robot measurements acquired at different vantage points during robot motion to determine initial pose, and a consensus based distributed particle filter (DPF) fusing statistics from local robot and neighbors to realize RL, are designed. In our system, by computing the pairwise relative pose between all robots in a team, the initialization strategy can determine an estimate of the initial pose of all robots with respect to a common reference frame and the corresponding covariance. The consensus based DPF allows determining the relative pose of all robots with significantly reduced computing costs. Experiments results on a team of differentially driven mobile robots show the effectiveness of the initialization strategy and highlight the low computation cost of the proposed approach.
2020 IEEE 23rd International Conference on Information Fusion (FUSION)