Boston Dynamics reveals new details about Atlas, its humanoid robot, and how it perceives the world around it.

Boston

Boston Dynamics has released new details about how its Atlas humanoid robot perceives and interacts with its surroundings. The robot uses a combination of cameras and advanced perception systems to identify objects, assess their positions, and adapt to changes in its environment, such as when items are moved or obstructed.

Atlas is designed to perform a variety of tasks beyond single-task training, utilizing 3D modeling and joint data to maintain awareness even when objects are partially blocked. Recent demonstrations also showcased Atlas's ability to learn in simulation using NVIDIA's Dextra RGB workflow, allowing it to grasp and manipulate a range of objects autonomously. These advancements reflect a broader industry shift towards more versatile and generally capable robots.

How Boston Dynamics' Atlas Humanoid robot sees the world

The latest video from Boston Dynamics shares new insights about how its Atlas humanoid robot perceives the world around it. We dig into the details and explain why Boston Dynamics and many others in the robotics industry are aiming to move away from training robots one task at a time and towards training that makes robots more generally useful and versatile. In the latest demo video Atlas is shown picking and placing car parts into their designated slots, an activity we've seen the robot do in previous videos but with new twists. Someone throws an engine cover down on the ground. Atlas looks around, identifies the item as an engine cover which is relevant to its task, spins around with some unusual footwork, picks up the engine cover, placing it in its rightful spot with a little punch. A bit more delicate than the punches we've seen thrown by Unitrix humanoid robots but hey maybe in time we'll see these robots square off in the ring. Oh and Atlas wrapped it all up by giving a thumbs up to the camera. Atlas's vision system includes most obviously a camera which helps the robot identify relevant objects to its assigned task as well as any potential hazards or boundaries to be avoided. We also see red and green overlaid over Atlas's point of view. Boston Dynamics says these key points represent the robots perception which enable it to pick and place auto parts properly even when Boston Dynamics employees are making changes to the environment while the robot is working. To be ready and prepared to react to any environmental changes, Atlas needs to be constantly updating its model of the world around it. To accompany its 2D picture of its environment, Atlas also constructs a 3D model to help determine how far away items are, how to orient itself and the items it's grabbing, and more. To keep track of an object's position even when the robots view of them is blocked by its arm or the slot that the engine cover is in, Atlas is able to combine data from its vision system with information from its joints to determine the position of its grippers. When Atlas looks at an object, it can also determine its pose by comparing it to 3D models of similar objects it's been trained on. This can help Atlas determine where an object belongs and how best to pick it up. All of this work is part of efforts to move away from training robots one task at a time towards training robots in a way that allows them to perform a variety of tasks off of just one type of training. This effort to find a more generalized approach to robot training was demonstrated in another video recently shared by Boston Dynamics, which shows Atlas's torso only mounted in front of a table to practice gripping a variety of objects. This fully autonomous demo was achieved using NVIDIA's Dextra RGB workflow, which involves training entirely in simulation before being put to use in the real world. Atlas is shown grasping a variety of objects and even manages to stop and retry when it detects something going wrong. NVIDIA showed off its suite of robot training tools at this year's GPU technology conference. Let's go talk about robotics shall we? To see how NVIDIA helps teach robots how to be robots, check out this video right here. What do you think about how Atlas and robotics in general are developing? Let us know down in the comments. As always, thanks so much for watching. I'm your host Jesse Earl. See you next time with The Fam.

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