Control of two-wheeled humanoid robots poses several challenges due to the unstable dynamics of their mobile base and the coupling between upper and lower body dynamics. The problem is often faced in the literature with methods based on linearized or simplified models that fail in exploiting the whole body dynamic capabilities of the platform in use. In this work we tackle the problem of whole-body dynamic control for a mobile wheeled unstable humanoid robot. Compared to existing approaches based on on-line optimization to guarantee respect of the constraints, we propose a control method that takes into account the nominal constrained dynamics of the robot in the quasi-velocities through an internal model, thus reducing the computational burden. A computed-torque control law in the quasi-velocities is used to stabilize the robot around the upper position. We report on preliminary experimental results and on the method effectiveness in rejecting unknown external disturbances.

This paper presents a new approach to solve the Time-Optimal Path Tracking under limited joint range and bounds on velocity, acceleration and jerk. To obtain smooth and continuous accelerations, with beneficial effects for the load and wear on the actuators but a limited impact on performance, we state the minimum-time path tracking problem with the jerk as the control input. The main contribution of this paper is a formulation that includes the jerk constraints in the optimization problem and that, even if the resulting Non-Linear Programming (NLP) problem is non-convex, allows to perform an efficient and reliable convex relaxation using McCormick Envelopes. Simulations and experimental tests on two 7-DoF manipulators have been carried out to show the benefits of the proposed approach and to compare it to state-of-the-art techniques.

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