Human Leader and Robot Follower Team: Correcting Leader's Position from Follower's Heading

摘要

In multi-agent scenarios, there can be a disparity in the quality of position estimation amongst the various agents. Here, we consider the case of two agents - a leader and a follower - following the same path, in which the follower has a significantly better estimate of position and heading. This may be applicable to many situations, such as a robotic "mule" following a soldier. Another example is that of a convoy, in which only one vehicle (not necessarily the leading one) is instrumented with precision navigation instruments while all other vehicles use lower-precision instruments. We present an algorithm, called Follower-derived Heading Correction (FDHC), which substantially improves estimates of the leader's heading and, subsequently, position. Specifically, FHDC produces a very accurate estimate of heading errors caused by slow-changing errors (e.g., those caused by drift in gyros) of the leader's navigation system and corrects those errors.