Rm-Code: Proprioceptive Real-Time Recursive Multi-Contact Detection, Isolation and Identification

Humanoid robots in unknown environments need to be able to quickly react to contacts in order to ensure safety of humans and their own hardware. For showing useful reactions to contacts, the robot needs information about possibly multiple contacts such as their respective contact locations and wrenches. In this paper, we introduce our algorithm rm-Code, a real-time multi-contact detection, isolation and identification algorithm for tree-structured floating base robots based on generalized external forces and (optional) external wrenches measured by force/torque sensors within the kinematic chain. Those entities have been deduced in the literature using proprioceptive sensing only. Furthermore, the algorithm is fast enough for online computation. To the best of our knowledge, this is the first algorithm combining all of these properties. Rm-Code is quantitatively evaluated in simulation. The results show that our solution is able to accurately solve the problem when fed with perfect input data. In a second step, possible sources of error in the presence of noisy input data are analyzed. It is concluded that purely proprioception based contact isolation and identification in the multi-contact case has certain limitations under realistic conditions. However, these limitations could be overcome easily by integrating simple link contact detection, e.g. bumpers or other similarly simple means.