2003
DOI: 10.1016/s0921-8890(02)00351-2
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Real time gait generation for autonomous humanoid robots: A case study for walking

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Cited by 51 publications
(21 citation statements)
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“…Vukboratovic first analyzed the torque required to achieve the joint movements from the energy point of view [65]. Capi generates the walking gait of the biped robot Bonten-Maru for the optimization target with the lowest energy and the minimum variation in joint torque [66]. The energy optimization method can fully develop the performance of bipedal robots and reduce the system requirements.…”
Section: Gait Planning Based On Energy Consumption Optimizationmentioning
confidence: 99%
“…Vukboratovic first analyzed the torque required to achieve the joint movements from the energy point of view [65]. Capi generates the walking gait of the biped robot Bonten-Maru for the optimization target with the lowest energy and the minimum variation in joint torque [66]. The energy optimization method can fully develop the performance of bipedal robots and reduce the system requirements.…”
Section: Gait Planning Based On Energy Consumption Optimizationmentioning
confidence: 99%
“…Meanwhile, the methods to realizing dynamic walking were presented in (Hasegawa et al, 2000, Lim et al, 2000. Other achievements are in prototyping biped locomotion, biped legged control and optimal gait locomotion (Goswani et al, 1997, Capi et al, 2003. Input energy is another important index for natural walking motion.…”
Section: Background and Motivationmentioning
confidence: 99%
“…Recently, an evolutionary optimization method, such as evolutionary programming (EP), genetic algorithm (GA) and so on have been identified to find the optimal solutions in a non-linear system. In the research with Bonten-Maru II, Capi (Capi et al, 2003, Nasu et al, 2007 has proposed a real time generation of humanoid robot optimal gait by using soft computing techniques. GA was employed to minimize the energy for humanoid robot gait.…”
Section: Background and Motivationmentioning
confidence: 99%
“…The core point of this control strategy was to constantly change gait and trajectory according to different environments and tasks as well as stability state of robot. A control simulation platform was established to obtain the optimal controller parameters, and all the proposed methods were finally verified through simulations and experiments [17,18] . Some researchers [19][20][21] studied and implemented a real-time robust balance control for a humanoid robot under environment disturbance, the robot with robust control can resist an external thrust, stand on a two-axis inclinable platform, or walk on a see-saw successfully.…”
Section: Introductionmentioning
confidence: 99%