Footstep Planning Based on Univector Field Method for Humanoid Robot
Proceedings of the FIRA RoboWorld Congress 2009 on Advances in Robotics
Evolutionary optimized footstep planning for humanoid robot
CIRA'09 Proceedings of the 8th IEEE international conference on Computational intelligence in robotics and automation
Fuzzy SVM learning control system considering time properties of biped walking samples
Engineering Applications of Artificial Intelligence
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In order to handle complex navigational commands, this paper proposes a novel algorithm that can modify a walking period and a step length in both sagittal and lateral planes. By allowing a variation of zero moment point (ZMP) over the convex hull of foot polygon, it is possible to change the center of mass (CM) position and velocity independently throughout the single support phase. This permits a range of dynamic walking motion, which is not achievable using the 3-D linear inverted pendulum mode (3D-LIPM). In addition, the proposed algorithm enables to determine the dynamic feasibility of desired motion via the construction of feasible region, which is explicitly computed from the current CM state with simple ZMP functions. Moreover, adopting the closed-form functions makes it possible to calculate the algorithm in real time. The effectiveness of the proposed algorithm is demonstrated through both computer simulation and experiment on the humanoid robot, HanSaRam-VII, developed at the Robot Intelligence Technology (RIT) laboratory, Korea Advanced Institute of Science and Technology (KAIST).