Optimal Control of a Differentially Flat Two-Dimensional Spring-Loaded Inverted Pendulum Model

2020 ◽  
Vol 5 (2) ◽  
pp. 307-314 ◽  
Author(s):  
Hua Chen ◽  
Patrick M. Wensing ◽  
Wei Zhang
Author(s):  
Haoyu Ren ◽  
Qimin Li ◽  
Bing Liu ◽  
Zhenhuan Dou

High acceleration and extreme load are frequently appeared on high-speed locomotion of legged robot’s legs, imposing a challenging trade-off between weight and torque in leg design. This paper proposes a new design paradigm based on cable-drive and elastic linkage to solve the problem. The details of the design procedure are given, including the construction of the single leg. With the optimum design of the linkage mechanism, a combined index of the workspace and tracking error are used as object function, and taking geometrical design parameters of the linkage as optimization parameters. Based on the target workspace and the spring-loaded inverted pendulum model, the best foot trajectory in obstacle climbing and trotting gait are analyzed and illustrated. This paper built linkage cable-drive spring robot based on the legged module integration. Simulations and experiments indicate that linkage cable-drive spring robot performs stable trotting with control of the spring-loaded inverted pendulum model. Linkage cable-drive spring robot prototype experiments results are provided to verify the validity of the new method.


In the coming decades, humanoid robots will play a rising role in society. The present article discusses their walking control and obstacle avoidance on uneven terrain using enhanced spring-loaded inverted pendulum model (ESLIP). The SLIP model is enhanced by tuning it with an adaptive particle swarm optimization (APSO) approach. It helps the humanoid robot to reach closer to the obstacles in order to optimize the turning angle to optimize the path length. The desired trajectory, along with the sensory data, is provided to the SLIP model, which creates compatible COM (center of mass) dynamics for stable walking. This output is fed to APSO as input, which adjusts the placement of the foot during interaction with uneven surfaces and obstacles. It provides an optimum turning angle for shunning the obstacles and ensures the shortest path length. Simulation has been carried out in a 3D simulator based on the proposed controller and SLIP controller in uneven terrain.


2019 ◽  
Vol 16 (6) ◽  
pp. 172988141988570 ◽  
Author(s):  
Kathryn Walker ◽  
Helmut Hauser

Robust locomotion in a wide range of environments is still beyond the capabilities of robots. In this article, we explore how exploiting the soft morphology can be used to achieve stability in the commonly used spring-loaded inverted pendulum model. We evolve adaption rules that dictate how the attack angle and stiffness of the model should be changed to achieve stability for both offline and online learning over a range of starting conditions. The best evolved rules, for both the offline and online learning, are able to find stability from a significantly wider range of starting conditions when compared to an un-adapting model. This is achieved through the interplay between adapting both the control and the soft morphological parameters. We also show how when using the optimal online rule set, the spring-loaded inverted pendulum model is able to robustly withstand changes in ground level of up to 10 m downwards step size.


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