Visual servoing path planning via homogeneous forms and LMI optimizations
IEEE Transactions on Robotics
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Global path planning for robust visual servoing in complex environments
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Shortest paths for a robot with nonholonomic and field-of-view constraints
IEEE Transactions on Robotics
Neural network Reinforcement Learning for visual control of robot manipulators
Expert Systems with Applications: An International Journal
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Visual servoing consists of steering a robot from an initial to a desired location by exploiting the information provided by visual sensors. This paper deals with the problem of realizing visual servoing for robot manipulators taking into account constraints such as visibility, workspace (that is obstacle avoidance), and joint constraints, while minimizing a cost function such as spanned image area, trajectory length, and curvature. To solve this problem, a new path-planning scheme is proposed. First, a robust object reconstruction is computed from visual measurements which allows one to obtain feasible image trajectories. Second, the rotation path is parameterized through an extension of the Euler parameters that yields an equivalent expression of the rotation matrix as a quadratic function of unconstrained variables, hence, largely simplifying standard parameterizations which involve transcendental functions. Then, polynomials of arbitrary degree are used to complete the parametrization and formulate the desired constraints and costs as a general optimization problem. The optimal trajectory is followed by tracking the image trajectory with an IBVS controller combined with repulsive potential fields in order to fulfill the constraints in real conditions.