Optimized Control Strategies for Wheeled Humanoids and Mobile Manipulators
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Optimizing the control of articulated mobile robots leads to emergent behaviors that improve the effectiveness, efficiency and stability of wheeled humanoids and dynamically stable mobile manipulators. Our simulated results show that optimization over the target pose, height and control parameters results in effective strategies for standing, acceleration and deceleration. These strategies improve system performance by orders of magnitude over existing controllers. This paper presents a simple controller for robot motion and an optimization method for choosing its parameters. By using whole-body articulation, we achieve new skills such as standing and unprecedented levels of performance for acceleration and deceleration of the robot base. We describe a new control architecture, present a method for optimization, and illustrate its functionality through two distinct methods of simulation.