Optimization-Based Planning for Autonomous Traversal of Obstacles with Mobile Ground Robots

Mobile robotic platforms which are traversing unstructured environments with challenging uneven terrain are permanently endangered of falling over. Previous research on trajectory planning methods for the prevention of vehicle tip-over is mostly limited to basic mobility systems with only few degrees of freedom (DOF). This paper proposes a novel optimization-based planning approach that enables mobile robots to autonomously traverse obstacles and rough terrain more safely. A 3D world model as provided from external sensors like Lidar is used to compute a whole-body motion plan in advance by optimizing the trajectories of each joint. Active flipper tracks maximize ground contact for improved traction and, if available, manipulator arm joints are used to further improve stability metrics. Additional constraints prevent collisions with the environment and the robot itself. The presented approach makes only few assumptions about the robot’s configuration and is applicable to a wide range of wheeled or tracked platforms. This is demonstrated by experimental evaluation for two different robots in simulation and for one physical robot. In four different test scenarios it is shown, that the proposed approach effectively prevents vehicle tip-over during traversal of uneven ground