scholarly journals Optimal Foot Trajectory Planning of Bipedal Robots Based on a Measure of Falling

10.5772/52447 ◽  
2012 ◽  
Vol 9 (5) ◽  
pp. 172 ◽  
Author(s):  
Byoung-Ho Kim
2021 ◽  
pp. 825-835
Author(s):  
Shuyuan Shi ◽  
Shengchang Fang ◽  
Xuan Wu ◽  
Xiaojie Wang

2021 ◽  
Vol 11 (19) ◽  
pp. 9217
Author(s):  
Haichuang Xia ◽  
Xiaoping Zhang ◽  
Hong Zhang

Compared with wheeled and tracked robots, legged robots have better movement ability and are more suitable for the exploration of unknown environments. In order to further improve the adaptability of legged robots to complex terrains such as slopes, obstacle environments, and so on, this paper makes a new design of the legged robot’s foot sensing structure that can successfully provide accurate feedback of the landing information. Based on this information, a new foot trajectory planning method named three-element trajectory determination method is proposed. For each leg in one movement period, the three elements are the start point in the support phase, the end point in the support phase, and the joint angle changes in the transfer phase where the first two elements are used to control the height, distance, and direction of the movement, and the third element is used make decisions during the lifting process of the leg. For the support phase, the trajectory is described in Cartesian space, and a spline of linear function with parabolic blends is used. For the transfer phase, the trajectory is described in joint-space, and the joint angle function is designed as the superposition of the joint angle reverse-chronological function and the interpolation function which is obtained based on joint angle changes. As an important legged robot, a hexapod robot that we designed by ourselves with triangle gait is chosen to test the proposed foot trajectory planning method. Experiments show that, while the foot’s landing information can be read and based on the three-element trajectory planning method, the hexapod robot can achieve stable movement even in very complex scenes. Although the experiments are performed on a hexapod robot, our method is applicable to all forms of legged robots.


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