The goal of this paper is to demonstrate the capacity of model predictive control (MPC) to generate stable walking motions without the use of predefined footsteps. Building up on well-known MPC schemes for walking mot...
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The goal of this paper is to demonstrate the capacity of model predictive control (MPC) to generate stable walking motions without the use of predefined footsteps. Building up on well-known MPC schemes for walking motion generation, we show that a minimal modification of these schemes allows designing an online walking motion generator that can track a given reference speed of the robot and decide automatically the footstep placement. Simulation results are proposed on the HRP-2 humanoidrobot, showing a significant improvement over previous approaches. (C) Koninklijke Brill NV, Leiden and The robotics Society of Japan, 2010
We demonstrate in this paper our motion generation sheme for the generation of stable bipedal walking motions and we expand it to enhance its flexibility and independency. An algorithm for the control of appropriate o...
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ISBN:
(纸本)9781424466757
We demonstrate in this paper our motion generation sheme for the generation of stable bipedal walking motions and we expand it to enhance its flexibility and independency. An algorithm for the control of appropriate orientations of the feet and the trunk permits the robot to turn in a natural and safe way. Polygonal constraints on the positions of the computed feet positions serve to improve its reliability. A logic for the succession of the support phases and an algorithm for the automatic control of their orientations bridge the gap to more autonomy and to more practicability.
This paper presents a strategy for estimating the geometry of an interest object from a monocular video sequence acquired by a walking humanoid robot. The problem is solved using a space carving algorithm, which relie...
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ISBN:
(纸本)9781479971749
This paper presents a strategy for estimating the geometry of an interest object from a monocular video sequence acquired by a walking humanoid robot. The problem is solved using a space carving algorithm, which relies on both the accurate extraction of the occluding boundaries of the object as well as the precise estimation of the camera pose for each video frame. For data acquisition, a monocular visual-based control has been developed that drives the trajectory of the robot around an object placed on a small table. Due to the stepping of the humanoid, the recorded sequence is contaminated with artefacts that affect the correct extraction of contours along the video frames. To overcome this issue, a method that assigns a fitness score for each frame is proposed, delivering a subset of camera poses and video frames that produce consistent 3D shape estimations of the objects used for experimental evaluation.
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