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
Open-Set Object Recognition Using Mechanical Properties During Interaction
Pakorn Uttayopas, Xiaoxiao Cheng, Etienne Burdet
GREEMA: Proposal and Experimental Verification of Growing Robot by Eating Environmental MAterial for Landslide Disaster
Yusuke Tsunoda, Yuya Sato, Koichi Osuka
Multi-agent robotic systems and exploration algorithms: Applications for data collection in construction sites
Samuel A. Prieto, Nikolaos Giakoumidis, Borja Garcia de Soto
Adapt On-the-Go: Behavior Modulation for Single-Life Robot Deployment
Annie S. Chen, Govind Chada, Laura Smith, Archit Sharma, Zipeng Fu, Sergey Levine, Chelsea Finn