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Nonlinearities, differential constraints, and input limitations preclude the use of regular feedback control algorithms in a range of complex dynamic systems. This article introduces the concept of Regionally Growing Random Trees (RGRT) as a powerful tool that synergistically combines motion planning and control tasks. RGRT is a forest of Dynamics-based Rapidly Expanding Trees (DRETs) that grow in...
Usually in game theoretic formulations for robust motion planning, the model as well as the capabilities (input set) of all dynamic obstacles are assumed to be known. This paper aims to relax the assumption of known input set by proposing a unified framework for motion planning and admissible input set estimation. The proposed approach models every dynamic obstacle as an uncertain-constrained system...
Catching is one of the most complex tasks in the area of dynamic manipulation. Exact information on the position and orientation of a rigid object is crucial in order to accomplish manipulation tasks. Both motion planner and control strategy use these data to achieve the desired contact of a predefined surface with a nonprehensile end-effector, e.g. flat plate. This paper presents a multi-level approach...
The present paper proposes the motion planning based on “the dynamics shaping” for a robotic arm to hit the target robustly toward the desired direction, of which the concept is to shape the robot dynamics appropriately in order to accomplish the desired motion. According to the linear system theory, the positional error of the end-point converges onto near the singular vector corresponding to its...
The importance of the deformation and physics based deformation methods are continuously increasing in computer graphics area. However, the user interaction and reality using them is still insufficient for the various applications such as modeling process and game industry. In this paper, we propose physics based deformation technology under AR (augmented reality) environments to improve the effectiveness...
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