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
Real-World Robot Applications of Foundation Models: A Review
Kento Kawaharazuka, Tatsuya Matsushima, Andrew Gambardella, Jiaxian Guo, Chris Paxton, Andy Zeng
CURE: Simulation-Augmented Auto-Tuning in Robotics
Md Abir Hossen, Sonam Kharade, Jason M. O'Kane, Bradley Schmerl, David Garlan, Pooyan Jamshidi
Brain-Inspired Visual Odometry: Balancing Speed and Interpretability through a System of Systems Approach
Habib Boloorchi Tabrizi, Christopher Crick
How to Integrate Digital Twin and Virtual Reality in Robotics Systems? Design and Implementation for Providing Robotics Maintenance Services in Data Centers
Lin Xie, Hanyi Li