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
Athletic Mobile Manipulator System for Robotic Wheelchair Tennis
Zulfiqar Zaidi, Daniel Martin, Nathaniel Belles, Viacheslav Zakharov, Arjun Krishna, Kin Man Lee, Peter Wagstaff, Sumedh Naik, Matthew Sklar, Sugju Choi, Yoshiki Kakehi, Ruturaj Patil, Divya Mallemadugula, Florian Pesce, Peter Wilson, Wendell Hom, Matan Diamond, Bryan Zhao, Nina Moorman, Rohan Paleja, Letian Chen, Esmaeil Seraj, Matthew Gombolay
DALL-E-Bot: Introducing Web-Scale Diffusion Models to Robotics
Ivan Kapelyukh, Vitalis Vosylius, Edward Johns
Density Planner: Minimizing Collision Risk in Motion Planning with Dynamic Obstacles using Density-based Reachability
Laura Lützow, Yue Meng, Andres Chavez Armijos, Chuchu Fan
ProxNLP: a primal-dual augmented Lagrangian solver for nonlinear programming in Robotics and beyond
Wilson Jallet, Antoine Bambade, Nicolas Mansard, Justin Carpentier
Improving Assistive Robotics with Deep Reinforcement Learning
Yash Jakhotiya, Iman Haque
When Robotics Meets Wireless Communications: An Introductory Tutorial
Daniel Bonilla Licea, Mounir Ghogho, Martin Saska
ElasticROS: An Elastically Collaborative Robot Operation System for Fog and Cloud Robotics
Boyi Liu