Robot Motion Planning
Dynamic Motion Planning for Mobile Robots Using Potential Field Method
Autonomous Robots
CERMA '06 Proceedings of the Electronics, Robotics and Automotive Mechanics Conference - Volume 01
Tracking-error model-based predictive control for mobile robots in real time
Robotics and Autonomous Systems
Trajectory Tracking Control of Wheeled Mobile Robots Based on the Artificial Potential Field
ICNC '08 Proceedings of the 2008 Fourth International Conference on Natural Computation - Volume 07
Control of a nonholonomic mobile robot using neural networks
IEEE Transactions on Neural Networks
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A new approach for navigation of mobile robots in dynamic environments by using Linear Algebra Theory, Numerical Methods, and a modification of the Force Field Method is presented in this paper. The controller design is based on the dynamic model of a unicycle-like nonholonomic mobile robot. Previous studies very often ignore the dynamics of mobile robots and suffer from algorithmic singularities. Simulation and experimentation results confirm the feasibility and the effectiveness of the proposed controller and the advantages of the dynamic model use. By using this new strategy, the robot is able to adapt its behavior at the available knowing level and it can navigate in a safe way, minimizing the tracking error.