?? More Realistic Robotic Simulation! ?? Reinforcement learning has revolutionized quadrupedal locomotion, with simulators like #RaiSim playing a key role in training robust control policies. ?? However, recent findings reveal that RaiSim does not fully comply with the maximum dissipation principle (MDP)—a fundamental rule in simulating rigid contact interactions. ?? In our latest work, we propose a simple yet effective correction to RaiSim’s contact #algorithm, ensuring more physically accurate simulations. Our experiments demonstrate improved #consistency, paving the way for more reliable #robotic training environments. ?? Read more about our approach and findings: https://lnkd.in/dU24Hh-n #AGIMUSproject #Simulator #AI #Paper #Technologyinnovations
Impressive!
Convince Project, PILLAR-Robots, IntelliMan Project, CORESENSE, RegoProject, Sestosenso, euROBIN project,Adra - AI-Data-Robotics-Association, AI-on-Demand Platform CAIRNE MANOLO Project LAAS-CNRS, Inria, PAL Robotics PAL France, Q-PLAN INTERNATIONAL, Airbus, THIMM Obaly k.s., Czech Institute of Informatics, Robotics and Cybernetics, KLEEMANN