This video highlights work to date on the Yobotics-IHMC lower body humanoid robot. The robot is a twelve degree-of-freedom robot with force controllable series elastic actuators at each degree of freedom. Control algorithms utilize virtual model control, and foot placement is determined using capture regions. The robot can recover from moderate disturbances and walk on flat ground. Ongoing work is focused on improving robustness to disturbances, walking more quickly and efficiently, and walking over rough terrain.

Researchers at IHMC and Honda Research Institute are developing techniques for learning capture points for bipedal push recovery. A capture point is a point on the ground where a biped can step to in order to stop. Humans are very adept at stepping to capture points, while most bipedal robots cannot recover from significant pushes. To calculate approximate capture point locations, we use the linear inverted pendulum model introduced by Kajita and Tani. For a point mass biped walking at a constant height, this model exactly predicts the capture point. However, for a distributed mass biped, it is only an approximation. In order to better predict capture points, we learn a correction function to the linear inverted pendulum model. We used two learning methods, one online and one offline, to improve capture point prediction. In the offline learning method, the robot is pushed multiple times with a given force magnitude and direction. In the online learning technique, we use a radial basis function to represent the learned offsets from the capture point predicted by the linear inverted pendulum model.

We present a controller for a quadrupedal robot statically walking on known rough terrain. The controller has both deliberative and reactive components for task specific control issues, such as impassable terrain and unmodeled foot slippage. The controller architecture supports multiple gaits, and we present both a stable omnidirectional gait and a faster directional gait. The robot successfully negotiates obstacles up to 7.5 cm (ap40% leg length) tall and navigates over rocky terrain.