Nonlinear Observability of Unicycle Multi-Agent Teams Subject to Sensor Bias and Environmental Disturbance
Larkin Heintzman, Ryan K. Williams · 2018
In this paper, we consider the problem of localizing a team of unicycle agents with collaborative ranging, onboard compass measurements, and access to a subset of agent positions. Unlike previous work, we study the general multi-agent localization problem where we would like to also simultaneously estimate compass errors and an environmental disturbance experienced by all agents. The motivating example is localizing a team of autonomous underwater vehicles (AUVs), where GPS is not available to all agents, acoustic range-only measurements are common, and compass bias as well as environmental disturbances must be overcome. Significant work has been done in cooperative localization, however the idea of localization under the described conditions has not received much attention. We approach this problem by first looking at the nonlinear observability matrix, then analyzing it to determine conditions for observability of the multi-agent system. We then reduce the observability matrix to a metric that we exploit for planning observability maximizing agent trajectories under sensor bias and environmental disturbance. We then close with simulations.