Mobile Robot
Mobile robots are autonomous systems designed to navigate and interact with their environment, with research focusing on improving their perception, navigation, and manipulation capabilities. Current efforts concentrate on enhancing robustness through sensor fusion (e.g., combining radar and vision data), efficient motion planning guided by natural language instructions or reinforcement learning, and reliable localization using techniques like visual odometry and polygon-based mapping. These advancements are crucial for expanding the applications of mobile robots in diverse fields, including manufacturing, logistics, healthcare, and exploration, by enabling safer, more efficient, and adaptable operation in complex and dynamic settings.
Papers
Flow-Based Integrated Assignment and Path-Finding for Mobile Robot Sorting Systems
Yiduo Huang, Zuojun Shen
Path Planning Under Uncertainty to Localize mmWave Sources
Kai Pfeiffer, Yuze Jia, Mingsheng Yin, Akshaj Kumar Veldanda, Yaqi Hu, Amee Trivedi, Jeff Zhang, Siddharth Garg, Elza Erkip, Sundeep Rangan, Ludovic Righetti