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To enable robust dynamic walking on the Atlas robot, we extend our previous work by adding a receding-horizon component. The new controller consists of three hierarchies: a center of mass (CoM) trajectory planner that follows a sequence of desired foot steps, a receding-horizon controller that optimizes the next foot placement to minimize future CoM tracking errors, and an inverse dynamics based full...
We describe the design and hardware implementation of our walking and manipulation controllers that are based on a cascade of online optimizations. A virtual force acting at the robot's center of mass (CoM) is estimated and used to compensated for modeling errors of the CoM and unplanned external forces. The proposed controllers have been implemented on the Atlas robot, a full size humanoid robot...
We introduce a center of mass estimator, and its application in full body inverse dynamics control, fall detection and fall prevention for humanoid robots. We use the Linear Inverted Pendulum Model dynamics with an offset to predict the center of mass motion. This offset can be interpreted as a modelling error on the center of mass position, or an external force exerted on the center of mass of the...
One popular approach to controlling humanoid robots is through inverse kinematics (IK) with stiff joint position tracking. On the other hand, inverse dynamics (ID) based approaches have gained increasing acceptance by providing compliant motions and robustness to external perturbations. However, the performance of such methods is heavily dependent on high quality dynamic models, which are often very...
The ParkourBot climbs in a planar reduced-gravity vertical chute by leaping back and forth between the chute’s two parallel walls. The ParkourBot is comprised of a body with two springy legs and its controls consist of leg angles at touchdown and the energy stored in them. During flight, the robot stores elastic potential energy in its springy legs and then converts this potential energy in to kinetic...
We present an optimization based real-time walking controller for a full size humanoid robot. The controller consists of two levels of optimization, a high level trajectory optimizer that reasons about center of mass and swing foot trajectories, and a low level controller that tracks those trajectories by solving a floating base full body inverse dynamics problem using Quadratic Programming. Our controller...
The ParkourBot is an efficient and dynamic climbing robot. The robot comprises two springy legs connected to a body. Leg angle and spring tension are independently controlled. The robot climbs between two parallel walls by leaping from one wall to the other. During flight, the robot stores elastic energy in its springy legs and automatically releases the energy to “kick off” the wall during touch...
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