Search Results - subject:"collision avoidance"

Harnessing the power of machine learning for AIS data-driven maritime research : a comprehensive review

Yang, Ying; Liu, Yang - In: Transportation research : an international journal 183 (2024), pp. 1-17

Persistent link: https://www.econbiz.de/10015078088

Coordination of electrical drilling machines in open-pit mines : a constraint programming approach

Maftah, Mohamed; Gamache, Michel; Agard, Bruno; … - 2024

Persistent link: https://www.econbiz.de/10015073666

Decentralised protocols for autonomous mobile robots in material handling : inductive learnings from centralised controller

Kim, Byeongmok; Kim, Yonggab; Lee, Seokcheon - In: International journal of production research 63 (2025) 4, pp. 1372-1398

Persistent link: https://www.econbiz.de/10015202277

Topology-preserved distorted space path planning

Xie, Yangmin; Yang, Qiaoni; Zhou, Rui; Cao, Zhiyan; … - In: Industrial Robot: the international journal of robotics … 51 (2024) 6, pp. 973-984

Purpose Fast obstacle avoidance path planning is a challenging task for multijoint robots navigating through cluttered workspaces. This paper aims to address this issue by proposing an improved path-planning method based on the distorted space (DS) method, specifically designed for...

Persistent link: https://www.econbiz.de/10015348359

Human-following task without a prior map

Zhou, Zhiqiang; Fu, Yong; Wu, Wei - In: Industrial Robot: the international journal of robotics … 51 (2024) 6, pp. 960-972

Purpose The human-following task is a fundamental function in human–robot collaboration. It requires a robot to recognize and locate a target person, plan a path and avoid obstacles. To enhance the applicability of the human-following task in various scenarios, it should not rely on a prior...

Persistent link: https://www.econbiz.de/10015348420

Rolling cargo management using a deep reinforcement learning approach

Oucheikh, Rachid; Löfström, Tuwe; Ahlberg, Ernst; … - In: Logistics 5 (2021) 1, pp. 1-18

Loading and unloading rolling cargo in roll-on/roll-off are important and very recurrent operations in maritime logistics. In this paper, we apply state-of-the-art deep reinforcement learning algorithms to automate these operations in a complex and real environment. The objective is to teach an...

Persistent link: https://www.econbiz.de/10015194823

Rolling cargo management using a deep reinforcement learning approach

Oucheikh, Rachid; Löfström, Tuwe; Ahlberg, Ernst; … - In: Logistics 5 (2021) 1/10, pp. 1-18

Persistent link: https://www.econbiz.de/10012488561

A robust human target following system in corridor environment based on wall detection

Li, Ruifeng; Wu, Wei - In: Industrial Robot: the international journal of robotics … 51 (2023) 1, pp. 34-43

Purpose In corridor environments, human-following robot encounter difficulties when the target turning around at the corridor intersections, as walls may cause complete occlusion. This paper aims to propose a collision-free following system for robot to track humans in corridors without a prior...

Persistent link: https://www.econbiz.de/10015348370

Collision avoidance control for redundant manipulators in construction operations: a null-space-based task-priority adjustment approach

Wu, Yi; Jia, Xiaohui; Li, Tiejun; Xu, Chao; Liu, Jinyue - In: Industrial Robot: the international journal of robotics … 51 (2023) 1, pp. 73-90

Purpose This paper aims to use redundant manipulators to solve the challenge of collision avoidance in construction … defining the “link space,” and then the priority of the collision avoidance task and the end-effector task is adjusted … manipulator welding tasks. Originality/value A new formula for task priority adjustment for collision avoidance of redundant …

Persistent link: https://www.econbiz.de/10015348371

A hybrid obstacle avoidance method for mobile robot navigation in unstructured environment

Zhou, Huaidong; Feng, Pengbo; Chou, Wusheng - In: Industrial Robot: the international journal of robotics … 50 (2022) 1, pp. 94-106

Purpose Wheeled mobile robots (WMR) are the most widely used robots. Avoiding obstacles in unstructured environments, especially dynamic obstacles such as pedestrians, is a serious challenge for WMR. This paper aims to present a hybrid obstacle avoidance method that combines an informed-rapidly...

Persistent link: https://www.econbiz.de/10014835571