A general framework of motion planning for redundant robot manipulator based on deep reinforcement learning

X Li, H Liu, M Dong - IEEE Transactions on Industrial …, 2021 - ieeexplore.ieee.org
Motion planning and its optimization is vital and difficult for redundant robot manipulator in
an environment with obstacles. In this article, a general motion planning framework that …

A review of recent trend in motion planning of industrial robots

MG Tamizi, M Yaghoubi, H Najjaran - International Journal of Intelligent …, 2023 - Springer
Motion planning is an integral part of each robotic system. It is critical to develop an effective
motion in order to achieve a successful performance. The ability to generate a smooth …

A motion planning algorithm for redundant manipulators using rapidly exploring randomized trees and artificial potential fields

A Sepehri, AM Moghaddam - IEEE Access, 2021 - ieeexplore.ieee.org
This paper presents a novel motion planner for redundant robotic manipulators by utilizing
rapidly exploring randomized trees and artificial potential fields. Rapidly exploring …

Obstacle avoidance of redundant manipulators using neural networks based reinforcement learning

M Duguleana, FG Barbuceanu, A Teirelbar… - Robotics and Computer …, 2012 - Elsevier
This paper proposes a new approach for solving the problem of obstacle avoidance during
manipulation tasks performed by redundant manipulators. The developed solution is based …

Path planning for multi-Arm Manipulators using Soft Actor-Critic algorithm with position prediction of moving obstacles via LSTM

KW Park, MS Kim, JS Kim, JH Park - Applied Sciences, 2022 - mdpi.com
This paper presents a deep reinforcement learning-based path planning algorithm for the
multi-arm robot manipulator when there are both fixed and moving obstacles in the …

Path planning for multi-arm manipulators using deep reinforcement learning: Soft actor–critic with hindsight experience replay

E Prianto, MS Kim, JH Park, JH Bae, JS Kim - Sensors, 2020 - mdpi.com
Since path planning for multi-arm manipulators is a complicated high-dimensional problem,
effective and fast path generation is not easy for the arbitrarily given start and goal locations …

Deep reinforcement learning-based path planning for multi-arm manipulators with periodically moving obstacles

E Prianto, JH Park, JH Bae, JS Kim - Applied Sciences, 2021 - mdpi.com
In the workspace of robot manipulators in practice, it is common that there are both static and
periodic moving obstacles. Existing results in the literature have been focusing mainly on the …

Optimization-based motion planning of mobile manipulator with high degree of kinematic redundancy

J Liao, F Huang, Z Chen, B Yao - International Journal of Intelligent …, 2019 - Springer
With the integration of mobility and manipulation, mobile manipulator constructed by mobile
platform and manipulator has become a potential solution for the fields of industrial …

Collision-free path planning for welding manipulator via hybrid algorithm of deep reinforcement learning and inverse kinematics

J Zhong, T Wang, L Cheng - Complex & Intelligent Systems, 2021 - Springer
In actual welding scenarios, an effective path planner is needed to find a collision-free path
in the configuration space for the welding manipulator with obstacles around. However, as a …

Motion planning of robot manipulators for a smoother path using a twin delayed deep deterministic policy gradient with hindsight experience replay

MS Kim, DK Han, JH Park, JS Kim - Applied Sciences, 2020 - mdpi.com
In order to enhance performance of robot systems in the manufacturing industry, it is
essential to develop motion and task planning algorithms. Especially, it is important for the …