首页|Studies from Huazhong University of Science and Technology Reveal New Findings o n Robotics [Online Whole-stage Gait Planning Method for Biped Robots Based On Improved Variable Springloaded Inverted Pendulum With Finite-s ized Foot (Vslip-ff) ...]
Studies from Huazhong University of Science and Technology Reveal New Findings o n Robotics [Online Whole-stage Gait Planning Method for Biped Robots Based On Improved Variable Springloaded Inverted Pendulum With Finite-s ized Foot (Vslip-ff) ...]
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators publish new report on Ro botics. According to news reporting originating from Wuhan, People's Republic of China, by NewsRx correspondents, research stated, "Environmental adaptability a nd real-time control are significant to the actual application of biped robots. The current Spring-Loaded Inverted Pendulum (SLIP) walking exhibits the complian t interaction with environments." Financial support for this research came from National Natural Science Foundatio n of China (NSFC). Our news editors obtained a quote from the research from the Huazhong University of Science and Technology, "However, the movability and controllability of this model is limited owing to the lack of ankles. Moreover, complicated nonlinear o ptimization problems in gait generation bring difficulties to real-time control. To overcome these problems, this study proposes an online wholestage gait plann ing method to enhance the bipedal walking performance. Firstly, considering the role of ankles, this study applies the proposed template model called Variable S pring-Loaded Inverted Pendulum with Finite-sized Foot (VSLIP-FF) model. Then a F inite State Machine (FSM)-based gait pattern including the corresponding bio-ins pired gait strategies is established, which extends the single cyclic gait to th e whole-stage gait. Secondly, to realize real-time gait planning, an online gait generator based on a neural network is applied to reduce the calculational burd en. Finally, the method is applied on the simulation prototype and real robot pl atform for verification."
WuhanPeople's Republic of ChinaAsiaEmerging TechnologiesMachine LearningNano-robotRoboticsHuazhong Univers ity of Science and Technology
NETL
NSTL
