Abstract
In this paper, the problem of controlling a human-like bipedal robot while walking is studied. The control method commonly applied when controlling robots in general and bipedal robots in particular, was based on a dynamical model. This led to the need to accurately define the dynamical model of the robot. The activities of bipedal robots to replace humans, serve humans, or interact with humans are diverse and ever-changing. Accurate determination of the dynamical model of the robot is difficult because it is difficult to fully and accurately determine the dynamical quantities in the differential equations of motion of the robot. Additionally, another difficulty is that because the robot’s operation is always changing, the dynamical quantities also change. There have been a number of works applying fuzzy logic-based controllers and neural networks to control bipedal robots. These methods can overcome to some extent the uncertainties mentioned above. However, it is a challenge to build appropriate rule systems that ensure the control quality as well as the controller’s ability to perform easily and flexibly. In this paper, a method for building a fuzzy rule system suitable for bipedal robot control is proposed. The design of the motion trajectory for the robot according to the human gait and the analysis of dynamical factors affecting the equilibrium condition and the tracking trajectory were performed to provide informational data as well as parameters. Based on that, a fuzzy rule system and fuzzy controller was proposed and built, allowing a determination of the control force/moment without relying on the dynamical model of the robot. For evaluation, an exact controller based on the assumption of an accurate dynamical model, which was a two-feedback loop controller based on integrated inverse dynamics with proportional integral derivative, is also proposed. To confirm the validity of the proposed fuzzy rule system and fuzzy controller, computation and numerical simulation were performed for both types of controllers. Comparison of numerical simulation results showed that the fuzzy rule system and the fuzzy controller worked well. The proposed fuzzy rule system is simple and easy to apply.
Highlights
A bipedal robot has a structure with many degrees of freedom
An important feature of the dynamics problem is the relationship between motion and the applied force, which ensures the robot’s manipulative motion and at the same time ensures that the robot is in balance, i.e., maintaining the desired posture and state without falling
There are many studies on motion trajectory planning for bipedal robots based on different approaches [17,18,19,20,21,22], but due to the robot structure being positioned only by two feet on the ground with poor stability, a class of motion trajectory design problems was implemented taking into account the dynamic characteristics
Summary
A bipedal robot has a structure with many degrees of freedom. An important feature of bipedal robots is poor stability because the robot is supported by only two feet on the ground. An important feature of the dynamics problem is the relationship between motion and the applied force, which ensures the robot’s manipulative motion and at the same time ensures that the robot is in balance, i.e., maintaining the desired posture and state without falling This is closely related to the problem of designing the robot’s motion trajectory and controlling the robot. There are many studies on motion trajectory planning for bipedal robots based on different approaches [17,18,19,20,21,22], but due to the robot structure being positioned only by two feet on the ground with poor stability, a class of motion trajectory design problems was implemented taking into account the dynamic characteristics. Basing the design of the motion trajectory and the control a bipedal robot on the principle of the ZMP point has been widely applied.
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