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
Mapping Pipelines and Simultaneous Localization for Petrochemical Industry Robots
Mahta Akhyani
MEM: Multi-Modal Elevation Mapping for Robotics and Learning
Gian Erni, Jonas Frey, Takahiro Miki, Matias Mattamala, Marco Hutter
Semantic Scene Difference Detection in Daily Life Patroling by Mobile Robots using Pre-Trained Large-Scale Vision-Language Model
Yoshiki Obinata, Kento Kawaharazuka, Naoaki Kanazawa, Naoya Yamaguchi, Naoto Tsukamoto, Iori Yanokura, Shingo Kitagawa, Koki Shinjo, Kei Okada, Masayuki Inaba