A review of graph neural networks: concepts, architectures, techniques, challenges, datasets, applications, and future directions
Deep learning has seen significant growth recently and is now applied to a wide range of
conventional use cases, including graphs. Graph data provides relational information …
conventional use cases, including graphs. Graph data provides relational information …
RNN for repetitive motion generation of redundant robot manipulators: An orthogonal projection-based scheme
For the existing repetitive motion generation (RMG) schemes for kinematic control of
redundant manipulators, the position error always exists and fluctuates. This article gives an …
redundant manipulators, the position error always exists and fluctuates. This article gives an …
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 …
A data-driven cyclic-motion generation scheme for kinematic control of redundant manipulators
Redundant manipulators are no doubt indispensable devices in industrial production. There
are various works on the redundancy resolution of redundant manipulators in performing a …
are various works on the redundancy resolution of redundant manipulators in performing a …
An acceleration-level data-driven repetitive motion planning scheme for kinematic control of robots with unknown structure
It is generally considered that controlling a robot precisely becomes tough on the condition
of unknown structure information. Applying a data-driven approach to the robot control with …
of unknown structure information. Applying a data-driven approach to the robot control with …
Inter-robot management via neighboring robot sensing and measurement using a zeroing neural dynamics approach
B Liao, C Hua, Q Xu, X Cao, S Li - Expert Systems with Applications, 2024 - Elsevier
This paper proposes a complex number representation method for dynamically recording
robot positions and develops an optimization strategy for measuring and minimizing inter …
robot positions and develops an optimization strategy for measuring and minimizing inter …
Novel joint-drift-free scheme at acceleration level for robotic redundancy resolution with tracking error theoretically eliminated
In this article, three acceleration-level joint-drift-free (ALJDF) schemes for kinematic control
of redundant manipulators are proposed and analyzed from perspectives of dynamics and …
of redundant manipulators are proposed and analyzed from perspectives of dynamics and …
Analysis and application of modified ZNN design with robustness against harmonic noise
The Zhang neural network (ZNN) has recently realized remarkable success in solving time-
varying problems. Harmonic noise widely exists in industrial applications and can severely …
varying problems. Harmonic noise widely exists in industrial applications and can severely …
Nonlinear gradient neural network for solving system of linear equations
For purpose of solving system of linear equations (SoLE) more efficiently, a fast convergent
gradient neural network (FCGNN) model is designed and discussed in this paper. Different …
gradient neural network (FCGNN) model is designed and discussed in this paper. Different …
New joint-drift-free scheme aided with projected ZNN for motion generation of redundant robot manipulators perturbed by disturbances
Joint-drift problems could result in failures in executing task or even damage robots in actual
applications and different schemes have been presented to deal with such a knotty problem …
applications and different schemes have been presented to deal with such a knotty problem …