Humanoid Loco-Manipulations Using Combined Fast Dense 3D Tracking and SLAM with Wide-Angle Depth-Images
Kevin Chappellet, Masaki Murooka, Guillaume Caron, Fumio Kanehiro, Abderrahmane Kheddar
Abstract
To efficiently achieve complex humanoid loco- manipulation tasks in industrial contexts, we propose a combined vision-based tracker-localization interplay integrated as part of a task-space whole-body optimization control. To achieve good perception complementarity between manipulation and localization, a new fast dense 3D model-based tracking using wide-angle depth image is developed and used in conjunction with a simultaneous localization and mapping software. Our approach allows humanoid robots, targeted for industrial manufacturing, to manipulate and assemble large-scale objects while walking. It is assessed with experiments consisting in rolling and assembling in an unwinder a heavy and wide bobbin using bimanual grasping and bipedal locomotion at a time. This experimental use-case is found in some large-scale manufacturing where bobbins are enrolled with various materials (cables, papers, rubbers, etc.). The same experiments are made using two different humanoid robots of the same family.