A review of the literature on fuzzy-logic approaches for collision-free path planning of manipulator robots
In recent years, a large number of manipulator robots have been deployed to replace or
assist humans in many repetitive and dangerous tasks. Yet, these robots have complex …
assist humans in many repetitive and dangerous tasks. Yet, these robots have complex …
A survey on projection neural networks and their applications
Constrained optimization problems arise in numerous scientific and engineering
applications, and many papers on the online solution of constrained optimization problems …
applications, and many papers on the online solution of constrained optimization problems …
Modified primal-dual neural networks for motion control of redundant manipulators with dynamic rejection of harmonic noises
In recent decades, primal-dual neural networks, as a special type of recurrent neural
networks, have received great success in real-time manipulator control. However, noises are …
networks, have received great success in real-time manipulator control. However, noises are …
Dynamic neural networks for motion-force control of redundant manipulators: An optimization perspective
Accurate position-force control is a core and challenging problem in robotics, especially for
manipulators with redundant degrees of freedom (DOFs). For example, trajectory tracking …
manipulators with redundant degrees of freedom (DOFs). For example, trajectory tracking …
On generalized RMP scheme for redundant robot manipulators aided with dynamic neural networks and nonconvex bound constraints
In this paper, in order to analyze the existing repetitive motion planning (RMP) schemes for
kinematic control of redundant robot manipulators, a generalized RMP scheme, which …
kinematic control of redundant robot manipulators, a generalized RMP scheme, which …
New disturbance rejection constraint for redundant robot manipulators: An optimization perspective
Due to the property of multiple solutions, redundant robot manipulators are usually required
to simultaneously achieve multiple objectives in complex applications. The research of …
to simultaneously achieve multiple objectives in complex applications. The research of …
Recurrent neural network for kinematic control of redundant manipulators with periodic input disturbance and physical constraints
Input disturbances and physical constraints are important issues in the kinematic control of
redundant manipulators. In this paper, we propose a novel recurrent neural network to …
redundant manipulators. In this paper, we propose a novel recurrent neural network to …
Motion planning of manipulators for simultaneous obstacle avoidance and target tracking: An RNN approach with guaranteed performance
Motion planning is a core issuein the field of robotic control, which directly affects the
programming efficiency of robots. In this article, we study the motion planning problem of …
programming efficiency of robots. In this article, we study the motion planning problem of …
Mutual-collision-avoidance scheme synthesized by neural networks for dual redundant robot manipulators executing cooperative tasks
Collision between dual robot manipulators during working process will lead to task failure
and even robot damage. To avoid mutual collision of dual robot manipulators while doing …
and even robot damage. To avoid mutual collision of dual robot manipulators while doing …
Acceleration-level inequality-based MAN scheme for obstacle avoidance of redundant robot manipulators
In this paper, a new inequality-based criterion is proposed and investigated for obstacle
avoidance of redundant robot manipulators at the joint-acceleration level. By incorporating …
avoidance of redundant robot manipulators at the joint-acceleration level. By incorporating …