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Robotics industry

Advances in Robotics and Automation: Push-Grasp Policy Learning Using Equivariant Models and Grasp Score Optimization

Researchers at Northeastern University have made significant breakthroughs in push-grasp policy learning, a crucial aspect of robotics and automation. The study, funded by the JPMorgan Chase PhD Fellowship, National Science Foundation, and National Aeronautics & Space Administration, proposes a novel framework for joint pushing and grasping policy learning. This framework,