What does this research mean for the field?

An integrated motion planning approach combining A* global planning, predistribution priority scheduling, and an IDWA-APF local planner achieves superior performance and conflict resolution for multi-Forklift-AGVs compared to conventional methods. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

To develop an integrated collaborative motion planning and priority scheduling framework for multi-agent Forklift-AGVs to resolve deadlocks and generate kinematically feasible trajectories.

September 2, 2026Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science

Collaborative motion planning for multi Forklift-AGVs based on IDWA-APF and predistribution priority scheduling

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To develop an integrated collaborative motion planning and priority scheduling framework for multi-agent Forklift-AGVs to resolve deadlocks and generate kinematically feasible trajectories.
Generated smooth global trajectories for each vehicle using the A* algorithm combined with cubic polynomial piecewise fitting.
Pre-assigned motion priorities based on path quality and obstacles to resolve multi-agent coordination conflicts.
Implemented a local planning layer combining an improved dynamic window approach with artificial potential fields (IDWA-APF) for velocity sampling and dynamic obstacle avoidance.
Simulation experiments demonstrated superior trajectory generation and motion planning performance compared to conventional multi-vehicle navigation algorithms.
The integrated framework effectively resolved multi-agent deadlocks and maintained obstacle avoidance under operational kinematic constraints.

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Implication

Simulation study demonstrates improved trajectory efficiency and conflict resolution in multi-forklift automated guided vehicles, highlighting safer coordination in smart factories.

Cite This Study

Qiu et al. (2026) studied this question.

synapsesocial.com/papers/6a97e25ec562ede874ec6813 https://doi.org/10.1177/09544062261480820

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Implication

Simulation study demonstrates improved trajectory efficiency and conflict resolution in multi-forklift automated guided vehicles, highlighting safer coordination in smart factories.

Collaborative motion planning for multi Forklift-AGVs based on IDWA-APF and predistribution priority scheduling

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Discussion

Implication

Cite This Study

Collaborative motion planning for multi Forklift-AGVs based on IDWA-APF and predistribution priority scheduling

Key Points

Discussion

Implication

Cite This Study

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