Hibikino-Musashi@Home 2023 Team Description Paper
Tomoya Shiba, Akinobu Mizutani, Yuga Yano, Tomohiro Ono, Shoshi, Tokuno, Daiju Kanaoka, Yukiya Fukuda, Hayato Amano, Mayu Koresawa, Yoshifumi, Sakai, Ryogo Takemoto, Katsunori Tamai, Kazuo Nakahara, Hiroyuki Hayashi,, Satsuki Fujimatsu, Yusuke Mizoguchi, Moeno Anraku

TL;DR
Hibikino-Musashi@Home 2023 presents a comprehensive overview of their robot vision dataset generator, open-source development environment, and brain-inspired AI system aimed at home service robots.
Contribution
The paper introduces new tools and systems, including a dataset generator and AI architecture, for developing home service robots in a standard platform league.
Findings
Development of a robot vision dataset generator
Implementation of an open-source robot development environment
Proposal of a brain-inspired AI system for home robots
Abstract
This paper describes an overview of the techniques of Hibikino-Musashi@Home, which intends to participate in the domestic standard platform league. The team has developed a dataset generator for the training of a robot vision system and an open-source development environment running on a human support robot simulator. The robot system comprises self-developed libraries including those for motion synthesis and open-source software works on the robot operating system. The team aims to realize a home service robot that assists humans in a home, and continuously attend the competition to evaluate the developed system. The brain-inspired artificial intelligence system is also proposed for service robots which are expected to work in a real home environment.
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
TopicsRobotics and Automated Systems · Robotic Path Planning Algorithms · Robotics and Sensor-Based Localization
