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
Continuous Object State Recognition for Cooking Robots Using Pre-Trained Vision-Language Models and Black-box Optimization
Kento Kawaharazuka, Naoaki Kanazawa, Yoshiki Obinata, Kei Okada, Masayuki Inaba
Learning Barrier-Certified Polynomial Dynamical Systems for Obstacle Avoidance with Robots
Martin Schonger, Hugo T. M. Kussaba, Lingyun Chen, Luis Figueredo, Abdalla Swikir, Aude Billard, Sami Haddadin
Personalizing Interfaces to Humans with User-Friendly Priors
Benjamin A. Christie, Heramb Nemlekar, Dylan P. Losey
Data-driven architecture to encode information in the kinematics of robots and artificial avatars
Francesco De Lellis, Marco Coraggio, Nathan C. Foster, Riccardo Villa, Cristina Becchio, Mario di Bernardo
From Flies to Robots: Inverted Landing in Small Quadcopters with Dynamic Perching
Bryan Habas, Bo Cheng
MOSAIC: A Modular System for Assistive and Interactive Cooking
Huaxiaoyue Wang, Kushal Kedia, Juntao Ren, Rahma Abdullah, Atiksh Bhardwaj, Angela Chao, Kelly Y Chen, Nathaniel Chin, Prithwish Dan, Xinyi Fan, Gonzalo Gonzalez-Pumariega, Aditya Kompella, Maximus Adrian Pace, Yash Sharma, Xiangwan Sun, Neha Sunkara, Sanjiban Choudhury