Robotic System
Robotic systems research focuses on developing robots capable of performing complex tasks autonomously and reliably in diverse environments. Current efforts concentrate on improving robot perception (e.g., vision-language models for failure detection and reasoning), control (e.g., adaptive control for joint failures and force-aware trajectory planning), and planning (e.g., behavior tree expansion with LLMs and probabilistic automata for task specification). These advancements are significant for various applications, including manufacturing, agriculture, healthcare, and domestic assistance, driving improvements in efficiency, safety, and human-robot collaboration.
Papers
Creative Robot Tool Use with Large Language Models
Mengdi Xu, Peide Huang, Wenhao Yu, Shiqi Liu, Xilun Zhang, Yaru Niu, Tingnan Zhang, Fei Xia, Jie Tan, Ding Zhao
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, Mayo Suzuka, Lu Shen, Kohei Maeda, Fumiya Matsuzaki, Ikuya Matsumoto, Kazuya Murai, Kosei Isomoto, Kim Minje, Yuichiro Tanaka, Takashi Morie, Hakaru Tamukoh
STOPNet: Multiview-based 6-DoF Suction Detection for Transparent Objects on Production Lines
Yuxuan Kuang, Qin Han, Danshi Li, Qiyu Dai, Lian Ding, Dong Sun, Hanlin Zhao, He Wang
One Problem, One Solution: Unifying Robot and Environment Design Optimization
Jan Baumgärtner, Gajanan Kanagalingam, Alexander Puchtaand Jürgen Fleischer