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Frontal Plane Balance Control of a Biped Robot Based on Human Balancing Strategy
Dehghani Tafti, Mohammad Reza | 2012
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- Type of Document: M.Sc. Thesis
- Language: Farsi
- Document No: 42866 (08)
- University: Sharif University of Technology
- Department: Mechanical Engineering
- Advisor(s): Farahmand, Farzam; Hoviattalab, Maryam
- Abstract:
- The capability to control and maintain upright posture is a fundamental requirement for humanoid robots. Although many control algorithms were successfully presented, it seems developing a new controller inspired from human balance strategy would greatly improve performance and reduce energy consumption. To study the control strategy used by human nerves system more precisely, a balancing exercise was designed and implemented. Five human subjects were asked to stand on an unstable tilting board and balance the board. Instantaneous Eulerian angles of body segments of human subjects were captured by utilizing Xsense orientation sensors. A humanoid robot standing on the tilting board was models with seven links and five degrees of freedom in Simulink environment of MATLAB. Anthropometric data of a human with 80 Kg and 180 cm was assigned to model segments. Kinematic data of experiments were the inputs of inverse dynamic algorithm. The outputs are the joint actuating forces and torques. Kinematic and kinetic data were implemented in training ANFIS networks. Each network has 15 inputs and only one output. Output of each network is the actuating forces exerted to model joints. Several simulations were performed to evaluate the performance of the designed controller. The results indicated that the controller was capable of effectively maintain the upright balance when starting from different initial conditions. To validate control loop performance, kinematic data of one test subject was compared by simulation results.
- Keywords:
- Bipedal Robot ; Neuro Fuzzy Network ; Inverse Dynamics ; Adaptive Neuro-Fuzzy Inference System (ANFIS) ; Balancing Strategy ; Frontal Plane
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