Non Humanoid Robot
Non-humanoid robots encompass a diverse range of designs, from multi-legged robots inspired by insects to wheeled and even flapping-wing robots, all aiming to achieve efficient and adaptable locomotion and manipulation in various environments. Current research emphasizes improving robot autonomy through reinforcement learning, particularly for gait generation and task planning, often incorporating large language models (LLMs) for natural language instruction processing and human-robot interaction. These advancements are significant for expanding robotic capabilities in challenging tasks such as cooking, search and rescue, and collaborative assembly, ultimately impacting fields ranging from manufacturing and healthcare to exploration and disaster response.
Papers
Working with Trouble and Failures in Conversation between Humans and Robots (WTF 2023) & Is CUI Design Ready Yet?
Frank Förster, Marta Romeo, Patrick Holthaus, Maria Jose Galvez Trigo, Joel E. Fischer, Birthe Nesset, Christian Dondrup, Christine Murad, Cosmin Munteanu, Benjamin R. Cowan, Leigh Clark, Martin Porcheron, Heloisa Candello, Raina Langevin
Recognition of Heat-Induced Food State Changes by Time-Series Use of Vision-Language Model for Cooking Robot
Naoaki Kanazawa, Kento Kawaharazuka, Yoshiki Obinata, Kei Okada, Masayuki Inaba
CBCL-PR: A Cognitively Inspired Model for Class-Incremental Learning in Robotics
Ali Ayub, Alan R. Wagner
AirTouch: Towards Safe Human-Robot Interaction Using Air Pressure Feedback and IR Mocap System
Viktor Rakhmatulin, Denis Grankin, Mikhail Konenkov, Sergei Davidenko, Daria Trinitatova, Oleg Sautenkov, Dzmitry Tsetserukou
Discovering Adaptable Symbolic Algorithms from Scratch
Stephen Kelly, Daniel S. Park, Xingyou Song, Mitchell McIntire, Pranav Nashikkar, Ritam Guha, Wolfgang Banzhaf, Kalyanmoy Deb, Vishnu Naresh Boddeti, Jie Tan, Esteban Real