Autonomous Robot
Autonomous robots are being developed to perform complex tasks in diverse and unpredictable environments, focusing on robust navigation, adaptive behavior, and reliable operation. Current research emphasizes improving perception through advanced computer vision techniques (e.g., keypoint detection, neural radiance fields) and developing efficient planning algorithms (e.g., deep reinforcement learning, hierarchical decision networks, belief space search) that incorporate uncertainty and handle dynamic situations. These advancements are significant for various applications, including exploration, manufacturing, agriculture, and search and rescue, promising increased efficiency and safety in challenging real-world scenarios.
Papers
A General Safety Framework for Autonomous Manipulation in Human Environments
Jakob Thumm, Julian Balletshofer, Leonardo Maglanoc, Luis Muschal, Matthias Althoff
Digital Twin Enabled Runtime Verification for Autonomous Mobile Robots under Uncertainty
Joakim Schack Betzer, Jalil Boudjadar, Mirgita Frasheri, Prasad Talasila