A terrestrial robot that can maneuver rough terrain and scout places is very useful in mapping out unknown areas. It can also be used explore dangerous areas in place of humans. A terrestrial robot modeled after a scorpion will be able to traverse undetected and can be used for surveillance purposes. Therefore, this paper proposes modelling of a scorpion inspired robot and a reinforcement learning (RL) based controller for navigation. The robot scorpion uses serial four bar mechanisms for the legs movements. It also has an active tail and a movable claw. The controller is trained to navigate the robot scorpion to the target waypoint. The simulation results demonstrate efficient navigation of the robot scorpion.
@article{arxiv.2008.13712,
title = {Control of a Nature-inspired Scorpion using Reinforcement Learning},
author = {Aakriti Agrawal and V S Rajashekhar and Rohitkumar Arasanipalai and Debasish Ghose},
journal= {arXiv preprint arXiv:2008.13712},
year = {2020}
}