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
A hierarchical framework for collision avoidance in robot-assisted minimally invasive surgery
Jacinto Colan, Ana Davila, Khusniddin Fozilov, Yasuhisa Hasegawa
Industry 6.0: New Generation of Industry driven by Generative AI and Swarm of Heterogeneous Robots
Artem Lykov, Miguel Altamirano Cabrera, Mikhail Konenkov, Valerii Serpiva, Koffivi Fid`ele Gbagbe, Ali Alabbas, Aleksey Fedoseev, Luis Moreno, Muhammad Haris Khan, Ziang Guo, Dzmitry Tsetserukou
RPC: A Modular Framework for Robot Planning, Control, and Deployment
Seung Hyeon Bang, Carlos Gonzalez, Gabriel Moore, Dong Ho Kang, Mingyo Seo, Luis Sentis
Securing the Future: Exploring Privacy Risks and Security Questions in Robotic Systems
Diba Afroze, Yazhou Tu, Xiali Hei