{"version":"1.0","type":"rich","provider_name":"Acast","provider_url":"https://acast.com","height":250,"width":700,"html":"<iframe src=\"https://embed.acast.com/$/682b883cbc0e7581522caad7/68cc42e39c7ab07d623dc422?\" frameBorder=\"0\" width=\"700\" height=\"250\"></iframe>","title":"Simulated humanoid robots learn to hike rugged terrain autonomously","description":"<p>Training humanoid robots to hike could accelerate development of embodied AI for tasks like autonomous search and rescue, ecological monitoring in unexplored places and more, say University of Michigan researchers who developed an AI model that equips humanoids to hit the trails.&nbsp;</p><p><br></p><p>With their new AI framework called&nbsp;<a href=\"https://lego-h-humanoidrobothiking.github.io/\" rel=\"noopener noreferrer\" target=\"_blank\">LEGO-H</a>, the researchers trained simulated, camera-equipped Unitree Robotics humanoids to plan ahead, avoid obstacles, maintain posture and adjust speed and stride to uneven ground. This research was federally funded by the National Science Foundation.</p>","author_name":"Michigan Engineering "}