CHOICE: Coordinated Human-Object Interaction in Cluttered Environments for Pick-and-Place Actions
Jintao Lu, He Zhang, Yuting Ye, Takaaki Shiratori, Sebastian Starke, Taku Komura

TL;DR
This paper presents CHOICE, a hierarchical system combining planning and control methods to generate realistic, goal-driven human-object interactions in cluttered environments for pick-and-place tasks.
Contribution
It introduces a novel hierarchical framework with a bimanual scheduler, neural implicit planner, and a dynamic control model for realistic interaction synthesis.
Findings
System produces natural pick-and-place movements across diverse scenarios.
Effective handling of complex object geometries and cluttered layouts.
Improved realism and flexibility in human-object interaction animation.
Abstract
Animating human-scene interactions such as pick-and-place tasks in cluttered, complex layouts is a challenging task, with objects of a wide variation of geometries and articulation under scenarios with various obstacles. The main difficulty lies in the sparsity of the motion data compared to the wide variation of the objects and environments as well as the poor availability of transition motions between different tasks, increasing the complexity of the generalization to arbitrary conditions. To cope with this issue, we develop a system that tackles the interaction synthesis problem as a hierarchical goal-driven task. Firstly, we develop a bimanual scheduler that plans a set of keyframes for simultaneously controlling the two hands to efficiently achieve the pick-and-place task from an abstract goal signal such as the target object selected by the user. Next, we develop a neural implicit…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsSocial Robot Interaction and HRI · Human Motion and Animation · Human Pose and Action Recognition
