AI benchmark helps robots plan and complete their chores in the real world
No matter how sophisticated they are, robots can often be indecisive and struggle with multi-step chores in the real world. For example, if you tell a robot to tidy a messy room, it might understand the goal but not know where to grab each object. It could even end up inventing steps. To address these common mistakes, Microsoft and a group of academics have developed an AI benchmark system to improve the accuracy of robot planning. The details of their work are published in a paper on the arXiv preprint server.
Engineers aim to give robots a bit of common sense when faced with situations that push them off their trained path, so they can self-correct after missteps and carry on with their chores. The team's method connects robot motion data with the common sense knowledge of large language models, or…
A collaboration between NVIDIA and academic researchers is prepping robots for surgery. ORBIT-Surgical — developed by researchers from the University of Toronto, UC Berkeley, ETH Zurich, Georgia Tech and NVIDIA — is a simulation framework to train robots that could augment the skills of surgical teams while reducing surgeons’ cognitive…