Inverse kinematics and reflex based controller for body-limb coordination of a salamander-like robot walking on uneven terrain

Search and rescue (SAR) missions are being carried out by several types of robots. They include ground, marine and air vehicles depending on the terrain and mission to be tackled. A particular niche for SAR activities are shallow waters. They present high difficultly for conventional ground or marine robots because of the mix of water and ground. Such an environment is difficult to be accessed for a robot without some built-in amphibious capabilities. Our lab has experience in the design of amphibious salamander-like robots. In order to consider whether these robots would be suited for SAR missions in shallow waters, a key requirement is the ability to tackle rough terrains. In this paper we present a control framework for a highly redundant salamander-like robot. It involves bio-inspired spine control, inverse kinematics-based limb control, proper limb-spine coordination, reflex mechanisms and attitude control. The framework is validated in a simulation and on the real robot. In both cases, the robot is used in two different configurations: with and without its tail, in order to investigate how the tail (which is necessary for swimming) affects ground locomotion. With this exploration, we aim to set the precedent for improving the problem of dynamic locomotion of salamander-like robots over unperceived rough terrain. Our results confirm that the design of reflexes like stumbling and extension, combined with an attitude controller, allows for the improving of the performance of the robot in a generic rough terrain which includes stairs, holes and bumps with several levels of complexity adjusted according to the robot dimensions.

Published in:
2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 195-201
Presented at:
2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Hamburg, Germany, 28 September - 2 October 2015

 Record created 2016-03-09, last modified 2018-01-28

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