Motion Control for a Humanoid

Cílem této bakalářské práce je návrh algoritmu chůze pro humanoidního robota. V průběhu práce je zvolen robot a vhodný algoritmus chůze pro aplikaci. Následně je sestaveno simulační a vývojové prostředí. Na robotu je provedena regulace motorů a aplikován výpočet a zobrazení referenčního bodu "Zero moment point". Pro robot je navržen algoritmus pro zahájení chůze pomocí snížení těžiště a rozkývání robota v laterálním směru s frekvencí rovnou vlastní frekvenci. Poté je aplikována chůze robota na místě.Goal of this bachelor thesis is to design algorithm for a walking of a humanoid robot. During the thesis, the robot and the algorithm for the walking is chosen and a simulation and a development environment is set. The regulation of motors of the humanoid is tuned up and the zero moment point is computed and displayed. Starting sequence of the humanoid robot is designed with usage of a lowering and a swinging of pelvis. Therefore, walking on one spot is applied for a humanoid robot

Humanoid robot walking control on inclined planes

The humanoid bipedal structure is suitable for a assitive robot functioning in the human environment. However, the bipedal walk is a difficult control problem. Walking just on even floor is not satisfactory for the applicability of a humanoid robot. This paper presents a study on bipedal walk on inclined planes. A Zero Moment Point (ZMP) based reference generation technique is employed. The orientation of the feet is adjusted online by a fuzzy logic system to adapt to different walking surface slopes. This system uses a sampling time larger than the one of the joint space position controllers. The average value of the body pitch angle is used as the inputs to the fuzzy logic system. A foot pitch orientation compensator implemented independently for the two feet complements the fuzyy controller. A 12-degrees-of-freedom (DOF) biped robot model is used in the full-dynamics 3-D simulations. Simulations are carried out on even floor and inclined planes with different slopes. The results indicate that the control method presented is successful in enabling the robot to climb slopes of 8.5 degrees (15 percent grade)

Trajectory generation for multi-contact momentum-control

Simplified models of the dynamics such as the linear inverted pendulum model (LIPM) have proven to perform well for biped walking on flat ground. However, for more complex tasks the assumptions of these models can become limiting. For example, the LIPM does not allow for the control of contact forces independently, is limited to co-planar contacts and assumes that the angular momentum is zero. In this paper, we propose to use the full momentum equations of a humanoid robot in a trajectory optimization framework to plan its center of mass, linear and angular momentum trajectories. The model also allows for planning desired contact forces for each end-effector in arbitrary contact locations. We extend our previous results on LQR design for momentum control by computing the (linearized) optimal momentum feedback law in a receding horizon fashion. The resulting desired momentum and the associated feedback law are then used in a hierarchical whole body control approach. Simulation experiments show that the approach is computationally fast and is able to generate plans for locomotion on complex terrains while demonstrating good tracking performance for the full humanoid control