Dynamic Obstacle Avoidance for Multi-Robot HPB-CBS under Heterogeneous Motion Constraints.

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Title: Dynamic Obstacle Avoidance for Multi-Robot HPB-CBS under Heterogeneous Motion Constraints.
Authors: Gao, Changqing1 gcq@hnu.edu.cn, Fang, Qiu2 qfang@hnu.edu.cn, Zeng, Kui3 zk101@hnu.edu.cn, Lei, Haipeng4 446430855@qq.com, Jia, Zhihao5 jia13220716491@hnu.edu.cn, Liu, Xiaorui6 liuxiaorui@hnu.edu.cn
Source: Engineering Letters. Jun2026, Vol. 34 Issue 6, p2374-2384. 11p.
Subjects: Obstacle avoidance (Robotics), Robotic path planning, Scheduling, Robot kinematics
Abstract: To address heterogeneous kinematic models and dynamic task sequences in multi-agent path finding (MAPF) for heterogeneous multi-robot systems, this paper proposes a Heterogeneous Priority Batching Conflict-Based Search (HPBCBS) algorithm. We develop a dynamic heterogeneous priority model that quantitatively ranks robots by jointly considering obstacle-avoidance capability, task urgency, and sequence utility. Building on this model, we enhance the CBS framework with priority-aware conflict selection and a robot-body-based continuous-space conflict definition at the high level, and an improved hybrid A* planner that supports both Ackermannsteered and holonomic robots at the low level. Moreover, a priority-based batching strategy and a hybrid online scheduling mechanism that combines event-triggered and periodic replanning are introduced to handle dynamic changes. Simulation results show that, compared with CBS-BS2 and PP-SHA*, HPBCBS achieves higher success rates across diverse problem sizes and obstacle densities, while improving solution quality and scalability. [ABSTRACT FROM AUTHOR]
Copyright of Engineering Letters is the property of International Association of Engineers (IAENG) and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Dynamic Obstacle Avoidance for Multi-Robot HPB-CBS under Heterogeneous Motion Constraints.
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  Data: <searchLink fieldCode="AR" term="%22Gao%2C+Changqing%22">Gao, Changqing</searchLink><relatesTo>1</relatesTo><i> gcq@hnu.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Fang%2C+Qiu%22">Fang, Qiu</searchLink><relatesTo>2</relatesTo><i> qfang@hnu.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Zeng%2C+Kui%22">Zeng, Kui</searchLink><relatesTo>3</relatesTo><i> zk101@hnu.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Lei%2C+Haipeng%22">Lei, Haipeng</searchLink><relatesTo>4</relatesTo><i> 446430855@qq.com</i><br /><searchLink fieldCode="AR" term="%22Jia%2C+Zhihao%22">Jia, Zhihao</searchLink><relatesTo>5</relatesTo><i> jia13220716491@hnu.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Liu%2C+Xiaorui%22">Liu, Xiaorui</searchLink><relatesTo>6</relatesTo><i> liuxiaorui@hnu.edu.cn</i>
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  Data: <searchLink fieldCode="JN" term="%22Engineering+Letters%22">Engineering Letters</searchLink>. Jun2026, Vol. 34 Issue 6, p2374-2384. 11p.
– Name: Subject
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  Data: <searchLink fieldCode="DE" term="%22Obstacle+avoidance+%28Robotics%29%22">Obstacle avoidance (Robotics)</searchLink><br /><searchLink fieldCode="DE" term="%22Robotic+path+planning%22">Robotic path planning</searchLink><br /><searchLink fieldCode="DE" term="%22Scheduling%22">Scheduling</searchLink><br /><searchLink fieldCode="DE" term="%22Robot+kinematics%22">Robot kinematics</searchLink>
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  Label: Abstract
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  Data: To address heterogeneous kinematic models and dynamic task sequences in multi-agent path finding (MAPF) for heterogeneous multi-robot systems, this paper proposes a Heterogeneous Priority Batching Conflict-Based Search (HPBCBS) algorithm. We develop a dynamic heterogeneous priority model that quantitatively ranks robots by jointly considering obstacle-avoidance capability, task urgency, and sequence utility. Building on this model, we enhance the CBS framework with priority-aware conflict selection and a robot-body-based continuous-space conflict definition at the high level, and an improved hybrid A* planner that supports both Ackermannsteered and holonomic robots at the low level. Moreover, a priority-based batching strategy and a hybrid online scheduling mechanism that combines event-triggered and periodic replanning are introduced to handle dynamic changes. Simulation results show that, compared with CBS-BS2 and PP-SHA*, HPBCBS achieves higher success rates across diverse problem sizes and obstacle densities, while improving solution quality and scalability. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
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  Data: <i>Copyright of Engineering Letters is the property of International Association of Engineers (IAENG) and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Text: English
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      – SubjectFull: Robotic path planning
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      – SubjectFull: Scheduling
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      – SubjectFull: Robot kinematics
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              Text: Jun2026
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              Y: 2026
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