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RISS 인기검색어
- 검색키워드
- 저자 : Babak Ranjbar,Gholam Dashti,Ali Omidvar,Javad Mahmoodi,Hasan Karbasi (검색결과 2 건)
- 무료
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- 유료
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Robot Manipulator Path Planning Based on Intelligent Multi-resolution Potential Field
Babak Ranjbar,Javad Mahmoodi,Hasan Karbasi,Gholam Dashti,Ali Omidvar 보안공학연구지원센터(IJUNESST) 2015 International Journal of u- and e- Service, Scienc Vol.8 No.1
Robot path planning is an important part of the development of autonomous systems. Numerous strategies have been proposed in the literature regarding mobile robots but trajectory planning for manipulators is considerably more difficult since the entire structure can move and therefore produce collisions with surrounding obstacles. This paper presents an original solution and analytical comparison to path planning for manipulator arms. Path planning is executed in two parts: first, a global path is found to guide the end-effector in the environment using artificial potential fields and multi-resolution occupancy grids, then, a local path is determined for the entire robot structure by considering the kinematics of the robot as well as the repulsive forces of nearby obstacles in a fuzzy logic controller. Results are shown from a simulator that has been built for this purpose. The contribution of this research is to develop a robust solution for path planning with collision avoidance: one that can be used for various manipulator arms and environment configurations.
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Tuning New Fuzzy Control for Nonlinear Second Order System
Babak Ranjbar,Gholam Dashti,Ali Omidvar,Javad Mahmoodi,Hasan Karbasi 보안공학연구지원센터 2014 International Journal of Hybrid Information Techno Vol.7 No.6
Cognitive method is used in this research to create portfilo of movement robot manipulator. Gradient descent (GD) fuzzy controller was used and robot’s postures and trajectory were expected in MATLAB/SIMULINK environment. Fuzzy logic controller (FLC) is an influential nonlinear controller to certain and uncertain systems which it is based on artificial intelligent and computes the required torques using the nonlinear feedback control law. Practically a large amount of systems have uncertainties accordingly this method has a challenge. Linear proportional-integral-derivative (PID) controller is a significant combination nonlinear stable-robust controller under condition of partly uncertain dynamic parameters of system. This technique is used to control of highly nonlinear systems especially in nonlinear time varient nonlinear dynamic system. To compensate for the dependence on model-free parameters, PID methodology is used. The nonlinear model dynamic formulation problem in uncertain system can be solved by using PID theorem. Proportional-Derivative-Integral (PID) theory is used to estimate the system dynamic.
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