Fast Perception, Planning, and Execution for a Robotic Butler: Wheeled Humanoid M-Hubo
Moonyoung Lee, Yujin Heo, Jinyong Park, Hyun-Dae Yang Ho-Deok Jang,, Philipp Benz, Hyunsub Park, In So Kweon, Jun-Ho Oh

TL;DR
This paper presents a fast, integrated perception and planning system for a wheeled humanoid robot, enabling it to perform daily assistance tasks efficiently in real-world environments.
Contribution
It introduces a novel integration of 3D object detection with kinematic planning to significantly improve robot response speed for service tasks.
Findings
Robot can fetch objects at 24% of human speed
System demonstrated successfully in real-world and public settings
Enhanced perception and planning pipeline improves efficiency
Abstract
As the aging population grows at a rapid rate, there is an ever growing need for service robot platforms that can provide daily assistance at practical speed with reliable performance. In order to assist with daily tasks such as fetching a beverage, a service robot must be able to perceive its environment and generate corresponding motion trajectories. This becomes a challenging and computationally complex problem when the environment is unknown and thus the path planner must sample numerous trajectories that often are sub-optimal, extending the execution time. To address this issue, we propose a unique strategy of integrating a 3D object detection pipeline with a kinematically optimal manipulation planner to significantly increase speed performance at runtime. In addition, we develop a new robotic butler system for a wheeled humanoid that is capable of fetching requested objects at 24%…
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.
