It works by dragging and adjusting Spot's pre-programmed moves on a timeline. The video describes some of the movements that Spot can perform, including body, step, dynamic transition, and knee movements. Within each of those categories, there are subcategories of movements that can be dragged to the timeline.
BostonDynamics' mission is to imagine and create exceptional robots that enrich people's lives.
Building machines that can approximate the mobility, dexterity and agility of people and animals is a big challenge. Curiosity and respect for the natural world are at the heart of our work on robots. We see the products derived from this work as the next step in the human history of machine building to reduce danger, repetition and the physically difficult aspects of work. Do Boston Dynamics robots use artificial intelligence?.
Stretch has a box-like base with a set of wheels that can move in all directions. At the top of the base is a large robotic arm and a perception mast. The robotic arm has seven degrees of freedom and an array of suction cups that can grip and lift boxes. The perception mast uses cameras and sensors driven by computer vision to analyze its environment.
But the most interesting video was an unprecedented behind-the-scenes account of how Boston Dynamics engineers developed and trained Atlas to run the parkour track. The video shows some of Atlas's failures and is a break with the company's tradition of showing very polished results from this work. The video and an accompanying blog post provide very important information about the challenges of creating humanoid robots. Unlike BigDog, which is run by Boston Dynamics, LittleDog aims to be a test bed for other institutions.
Boston Dynamics has identified parkour as a perfect testing activity for Atlas, as the company works to make high-powered humanoid robots more dexterous. Boston Dynamics, which was once owned by Google's parent company Alphabet, and now the Japanese conglomerate SoftBank, has long kept its designs secret. Nicholas Roy, who leads the Robust Robotics Group at MIT and describes himself as a bit agitator because of his skepticism of some of the claims made about the power of deep learning, agrees with ARL robotics that deep learning approaches often cannot handle the kind of challenges that the Army has to be prepared for. In a new company video, bipedal robots can be seen jumping the levels of a stepped platform, running across and over a balance beam, and generally making most humans look like clods in comparison.
He has built his fame on his advanced research and a continuous stream of videos showing robots doing things that were previously thought impossible. Boston Dynamics causes a viral sensation every time it publishes a new video of one of its robots moving through the laboratory. He points to the response to a video in which Atlas appears trying to pick up a box, but with a Boston Dynamics employee moving it out of reach and pushing the robot with a hockey stick. Hyundai has already done extensive research into creating robots and autonomous vehicles that can navigate in various environments and terrains.
Atlas has inspired a series of parody videos on YouTube and more than a few jokes about taking control of a robot. If you want to act like a robotics expert when watching one of these videos, one of the first things you need to do is be critical about how Boston Dynamics, a private company rather than an academic entity, doesn't publish enough of its findings. But the software being developed for RoMan and other robots in ARL, called Adaptive Planner Parameter Learning (APPL), will probably be used first in autonomous driving and later in more complex robotic systems that could include mobile manipulators such as RoMan. We believe that the skills inherent in dance and parkour, such as agility, balance and perception, are fundamental to a wide variety of robot applications.
In chaotic, unknown, or ill-defined environments, reliance on rules makes robots notoriously bad at dealing with anything that cannot be accurately predicted and planned beforehand. In robotics, as in many other fields of science, engineers are looking for ways to avoid replicating nature in detail by taking shortcuts, creating models, and optimizing to achieve objectives. . .