Rescue robots are often equipped with chain drive and flipper systems, which greatly increase the effort of the operator to control the robot. As the use of flippers often consumes more time, the wear of the robot is increased due to the inefficient utilization of the flippers because the operator prioritizes speed within a search and rescue mission. In this paper, we propose an autonomous flipper controller that can be implemented on a low-level controller without the use of an embedded system with high computing power. For this, we use 3D-data of a ToF-LiDAR, project it onto a 2D-plane to estimate the slope of the terrain using linear least square regression. A set of rules then controls the flippers based on the robot’s tilt and IMU data. This approach was implemented and tested successfully on some test methods in our robotic lab and at the RoboCup competition.
|Number of pages||6|
|Publication status||Published - 27 Oct 2022|
|Event||Agile Robotics: Perception, Learning, Planning, and Control: Full Day IROS 2022 workshop, October 27 2022 - Kyoto International Conference Center (ICC Kyoto), Kyoto, Japan|
Duration: 23 Oct 2022 → 27 Oct 2022
|Workshop||Agile Robotics: Perception, Learning, Planning, and Control|
|Period||23.10.2022 → 27.10.2022|