Affordance-Based Multi-Contact Whole-Body Pose Sequence Planning for Humanoid Robots in Unknown Environments

Abstract

Despite impressive advances of humanoid robotics, the autonomous planning of whole-body loco-manipulation actions in unknown environments is still an open problem. In our previous work, we addressed two fundamental aspects related to this problem: 1) the autonomous detection of end-effector contact opportunities in unknown environments and 2) the goal-directed planning of multi-contact pose sequences, which can serve as the starting point for motion planning and control approaches of reduced complexity. Both problems suffer from the extensive amounts of possible solutions, particularly due to the complexity of humanoid robots and the multitude of available contact opportunities. In this paper, we propose a method for the planning of whole-body multi-contact tasks based on our previous work on vision-based detection of loco-manipulation affordances and whole-body multi-contact pose sequence planning. We demonstrate a combined approach for planning multi-contact pose sequences with a focus on the utilization of available end-effectors for stabilizing contacts with the environment during loco-manipulation tasks. The method is evaluated in simulation in multiple exemplary scenarios based on actual sensor data and the humanoid robot ARMAR-4.