Game theory for distributed IoV task offloading with fuzzy neural network in edge computing
X Xu, Q Jiang, P Zhang, X Cao… - … on Fuzzy Systems, 2022 - ieeexplore.ieee.org
The development of the Internet of vehicles (IoV) has spawned a series of driving assistance
services (eg, collision warning), which improves the safety and intelligence of transportation …
services (eg, collision warning), which improves the safety and intelligence of transportation …
Utilization of multilayer perceptron for determining the inverse kinematics of an industrial robotic manipulator
Inverse kinematic equations allow the determination of the joint angles necessary for the
robotic manipulator to place a tool into a predefined position. Determining this equation is …
robotic manipulator to place a tool into a predefined position. Determining this equation is …
[PDF][PDF] Performance Analysis of 4-DOF RPRR Robot Manipulator Actuation Strategy for Pick and Place Application in Healthcare Environment
Direct and indirect physical contact of humans and objects become the main medium of
transmissible diseases such as COVID-19. Some strategies have been proposed to mitigate …
transmissible diseases such as COVID-19. Some strategies have been proposed to mitigate …
A neural network based approach to inverse kinematics problem for general six-axis robots
Inverse kinematics problems (IKP) are ubiquitous in robotics for improved robot control in
widespread applications. However, the high non-linearity, complexity, and equation …
widespread applications. However, the high non-linearity, complexity, and equation …
Ikflow: Generating diverse inverse kinematics solutions
Inverse kinematics—finding joint poses that reach a given Cartesian-space end-effector
pose—is a fundamental operation in robotics, since goals and waypoints are typically …
pose—is a fundamental operation in robotics, since goals and waypoints are typically …
Motion generation for walking exoskeleton robot using multiple dynamic movement primitives sequences combined with reinforcement learning
P Zhang, J Zhang - Robotica, 2022 - cambridge.org
In order to assist patients with lower limb disabilities in normal walking, a new trajectory
learning scheme of limb exoskeleton robot based on dynamic movement primitives (DMP) …
learning scheme of limb exoskeleton robot based on dynamic movement primitives (DMP) …
Task accuracy enhancement for a surgical macro-micro manipulator with probabilistic neural networks and uncertainty minimization
F Cursi, W Bai, EM Yeatman… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Accurate robot kinematic modelling is a major component for autonomous robot control to
guarantee safety and precision during task execution. In surgical robotics complex robotic …
guarantee safety and precision during task execution. In surgical robotics complex robotic …
Augmented neural network for full robot kinematic modelling in SE (3)
Due to the increasing complexity of robotic structures, modelling robots is becoming more
and more challenging, and analytical models are very difficult to build. Machine learning …
and more challenging, and analytical models are very difficult to build. Machine learning …
Machine Learning sequential methodology for robot inverse kinematic modelling
FL Tagliani, N Pellegrini, F Aggogeri - Applied Sciences, 2022 - mdpi.com
The application of robots is growing in most countries, occupying a relevant place in
everyday environments. Robots are still affected by errors due to their limitations, which may …
everyday environments. Robots are still affected by errors due to their limitations, which may …
Learning inverse kinematics using neural computational primitives on neuromorphic hardware
Current low-latency neuromorphic processing systems hold great potential for developing
autonomous artificial agents. However, the variable nature and low precision of the …
autonomous artificial agents. However, the variable nature and low precision of the …