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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

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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.

Index terms

Visual Tracking Perception for Grasping and Manipulation Humanoid Robot Systems