Robotics Domain
Robotics research currently focuses on enhancing robot autonomy, safety, and dexterity, particularly in unstructured environments. Key areas include developing robust control algorithms (like Model Predictive Control and reinforcement learning), improving perception through advanced sensor fusion and generative models, and creating more efficient and adaptable robot designs. These advancements are driving progress in diverse applications such as agriculture, healthcare, and manufacturing, ultimately aiming to create more capable and reliable robots for a wider range of tasks.
Papers
A Game Between Two Identical Dubins Cars: Evading a Conic Sensor in Minimum Time
Ubaldo Ruiz
Metasensor: a proposal for sensor evolution in robotics
Michele Braccini
Undergraduate Robotics Education with General Instructors using a Student-Centered Personalized Learning Framework
Rui Wu, David J Feil-Seifer, Ponkoj C Shill, Hossein Jamali, Sergiu Dascalu, Fred Harris, Laura Rosof, Bryan Hutchins, Marjorie Campo Ringler, Zhen Zhu
Immersive Robot Programming Interface for Human-Guided Automation and Randomized Path Planning
Kaveh Malek, Claus Danielson, Fernando Moreu
RoboCasa: Large-Scale Simulation of Everyday Tasks for Generalist Robots
Soroush Nasiriany, Abhiram Maddukuri, Lance Zhang, Adeet Parikh, Aaron Lo, Abhishek Joshi, Ajay Mandlekar, Yuke Zhu
ROB 204: Introduction to Human-Robot Systems at the University of Michigan, Ann Arbor
Leia Stirling, Joseph Montgomery, Mark Draelos, Christoforos Mavrogiannis, Lionel P. Robert, Odest Chadwicke Jenkins
A Unification Between Deep-Learning Vision, Compartmental Dynamical Thermodynamics, and Robotic Manipulation for a Circular Economy
Federico Zocco, Wassim M. Haddad, Andrea Corti, Monica Malvezzi