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
Radar Meets Vision: Robustifying Monocular Metric Depth Prediction for Mobile Robotics
Marco Job, Thomas Stastny, Tim Kazik, Roland Siegwart, Michael Pantic
LASMP: Language Aided Subset Sampling Based Motion Planner
Saswati Bhattacharjee, Anirban Sinha, Chinwe Ekenna
Design and construction of a wireless robot that simulates head movements in cone beam computed tomography imaging
R. Baghbani, M. Ashoorirad, F. Salemi, Med Amine Laribi (COBRA), M. Mostafapoor