Abstract not found

Abstract — Mapping opaque and confined environments such as caves and pipes is a challenging problem for mobile robots because sensor information is severely limited to the immediate proximity of the robot due to the extreme environmental conditions. The robot must also be flexible and agile in unstructured environments while still providing accurate pose estimation. This paper presents a solution to mapping a 2-dimensional tube by using only a snake robot’s proprioceptive joint angle sensors. We assume that the tube is sufficiently smooth and that we know the tube width. We propose techniques for (1) pose estimation of a snake robot by using a self-posture motion model, (2) correcting error in pose estimation using only the snake’s internal configuration over time, and (3) building environmental features using only self-occupancy and contact detection. Our goal is to use the minimal amount of sensor information possible to build an accurate spatial map of the environment. We have tested the proposed techniques in simulated environments and experimental results show that they are both effective and efficient for mapping tube environments. We plan to extend these techniques to deal with more complex confined environments beyond single-path tubes. I.

Abstract—Manipulators with compliant actuation exhibit passive joint displacements when exposed to external forces or collisions. This paper demonstrates that this displacement information is sufficient to infer a coarse estimate of the location of an incidental collision. Three techniques for contact point detection are compared: a closed-form inference model based on a serial chain with joint springs, a variation on Self Posture Changeability, and an empirical memory-based model of joint trajectories. The methods were experimentally tested using a Shadow Hand on an industrial Motoman SDA10 arm to quantify localization performance, actively discover and avoid a thin obstacle and localize and grasp a cup. I.