Inequality-based Manipulator-Obstacle Avoidance Using the LVI-based Primal-dual Neural Network ... Abstract: An important issue in the motion planning and control ...
reviewed, especially the LVI-based primal-dual neural network. The inequality-based QP formulation and its solution for obstacle avoidance are substantiated ...
Their latest research is based on a dual neural network design (called primal-dual neural network -PDNN) which is able to converge to optimal solutions based on ...
This paper presents the algorithmic and computational aspects of inequality-based criteria/formulations for obstacle avoidance of PA10 robot arm. The ...
The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their ...
Simulative results based on the PA10 robot manipulator in the presence of window-shaped and point obstacles further demonstrate the efficacy and superiority ...
Two QP solvers, i.e., a simplified primal–dual neural network based on linear variational inequalities (LVI) and an LVI-based numerical algorithm, are ...
One important issue in motion planning and kinematic control of redundant manipulators is the real-time obstacle avoidance.
It can solve the redundancy resolution problem, control the dual manipulators to work simultaneously, and avoid the mutual collision of dual robot manipulators.
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What is the obstacle avoidance robot algorithm?
The repetitive motion planning scheme and the LVI-based primal–dual neural network are simulated successfully based on PA10 robot arm, with effectiveness ...