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1-16 of 16
Keywords: Obstacle avoidance
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Journal Articles
Industrial Robot 1–19.
Published: 02 June 2026
...Ankur Bhargava; Mohammad Suhaib; Ajay K.S. Singholi Purpose Autonomous mobile robots (AMRs) operating in dense and dynamically changing environments require robust navigation and reliable obstacle-avoidance capabilities. This study aims to propose an intelligent navigation framework to enable AMRs...
Journal Articles
Industrial Robot (2026) 53 (2): 432–448.
Published: 14 October 2025
... Licensed re-use rights only Drone navigation Path planning Hybrid algorithm Neighborhood dragonfly algorithm (NDA) Probability fuzzy logic (PFL) Obstacle avoidance Drones, also called as unmanned aerial vehicles (UAVs), have become inherent tools in a wide range of applications including...
Journal Articles
Industrial Robot (2025) 52 (3): 425–432.
Published: 12 December 2024
..., composite virtual forces are generated on the haptic device to enhance operational stability and prevents unintentional operations that could bring the robot into close proximity with obstacles. Findings The VF method can accomplish online obstacle avoidance and operation guidance. The experimental...
Journal Articles
Industrial Robot (2025) 52 (1): 9–17.
Published: 16 July 2024
... of dynamic obstacles. This paper aims to propose a dynamic obstacle avoidance method based on reinforcement learning to address real-time processing of dynamic obstacles. Design/methodology/approach This paper introduces an innovative method that introduces a feature extraction network that integrates...
Journal Articles
Industrial Robot (2024) 51 (5): 761–771.
Published: 07 May 2024
...) for obstacle avoidance for the robotic arm's end-effector. Design/methodology/approach A new method for constructing temporary attractive points in 3D has been introduced using the vector triple product approach, which generates the attractive moments that attract the end-effector to move toward it. Second...
Journal Articles
Industrial Robot (2024) 51 (2): 326–339.
Published: 18 January 2024
... obstacles, which benefits from a novel reference database update strategy. The user can test different obstacle avoidance trajectories in the current task until a satisfactory solution is found. Findings Experiments performed with the KUKA cobot for obstacle avoidance show that this approach can adapt...
Journal Articles
Industrial Robot (2022) 49 (6): 1089–1100.
Published: 30 March 2022
...) , and the set of preferred following angles is presented in Shanee et al. (2016) . However, after all efforts to develop human-following methods, a RABS to help the robot follow the STP effectively in various unknown environments with a real-time obstacle avoidance is still an open problem, especially...
Journal Articles
Industrial Robot (2022) 49 (2): 301–310.
Published: 29 October 2021
... a natural working environment and generate obstacle avoidance data for training. To ensure a smooth transfer to a real robot, the automatic domain randomization technique is used to generate randomly distributed environmental parameters through the obstacle avoidance simulation of virtual robots...
Journal Articles
Industrial Robot (2022) 49 (2): 271–279.
Published: 14 October 2021
... is locally optimized. The whole obstacle avoidance process is based on the improved artificial potential field method, applied during the mechanical arm path planning action, along the motion from the starting point to the target point. Findings Simulation results show that the algorithm in this paper...
Journal Articles
Industrial Robot (2021) 48 (3): 423–441.
Published: 08 April 2021
... at the minimum required time, collision-free obstacle avoidance in static and dynamic environments and reaching to the static and dynamic goals. The proposed navigational controller performs linearly and nonlinearly both with reduced error-based objective function by Riemannian metric and scalar curvature...
Journal Articles
Industrial Robot (2020) 47 (6): 801–811.
Published: 18 October 2019
... and the experimental results demonstrate that the improved fuzzy optimized Q-Learning obstacle avoidance algorithm is feasible and effective. Originality/value The improved fuzzy optimized Q-Learning (FOQL) algorithm is used to solve the avoidance obstacles problem of the robot in the environment. To reduce...
Journal Articles
Industrial Robot (2020) 47 (2): 253–265.
Published: 02 September 2019
...Rupeng Yuan; Fuhai Zhang; Jiadi Qu; Guozhi Li; Yili Fu Purpose This paper aims to provide a novel obstacle avoidance method based on multi-information inflation map. Design/methodology/approach In this paper, the multi-information inflation map is introduced, which considers different...
Journal Articles
Industrial Robot (2019) 46 (2): 211–222.
Published: 07 May 2019
... and tracking control (ILTPTC) framework for autonomous vehicles driving along a reference path with obstacle avoidance is presented in Li et al. (2017) . However, they do not consider the interactions between the ground and the tire and, in fact, the trajectory planning is limited to the generation...
Journal Articles
Industrial Robot (2018) 45 (5): 688–702.
Published: 16 October 2018
... footprints. This diversifies its areas of application to both indoor and outdoor environments especially with very narrow spaces, sharp turns and inclined surfaces where its multi-wheel counterparts feel difficult to perform. Originality/value A new obstacle avoidance and path planning algorithm through...
Journal Articles
Industrial Robot (2018) 45 (2): 227–236.
Published: 09 February 2018
...Qiang Zhou; Danping Zou; Peilin Liu Purpose This paper aims to develop an obstacle avoidance system for a multi-rotor micro aerial vehicle (MAV) that flies in indoor environments which usually contain transparent, texture-less or moving objects. Design/methodology/approach The system adopts...
Journal Articles
Industrial Robot (2016) 43 (1): 33–47.
Published: 18 January 2016
... of the presented scenarios which contain both computer and real-world experiments for complicated crowded environments indicate the merits of the suggested methodology in terms of its near-optimal behavior, successful obstacle avoidance both in static and dynamic environments and reaching to the goal pose...
