Automated Return System and Task Distribution Method

Task Allocation Technology for Heterogeneous Automated Transport Systems Combining Load Constraints and Heuristic Optimization

This technology is an automated transport system and task allocation method that optimizes route and task assignment by setting vertices for multiple heterogeneous automated guided vehicles (AGVs), calculating travel costs based on vehicle-specific structural characteristics, and integrating primal-dual heuristic techniques with load constraints.

In heterogeneous AGV systems with varying structural characteristics and load capacities, there has been a challenge in maximizing overall efficiency while minimizing the computational load required for task allocation and path planning.

This technology proposes a two-stage optimization process: first, setting initial vehicle positions and task nodes as vertices to obtain a travel cost matrix for initial allocation via heuristic techniques, and second, redistributing tasks by applying constraints that compare load capacity with required loads. It can be applied to unmanned transport systems in smart factories and logistics warehouses, significantly increasing throughput in environments where heterogeneous vehicles operate together.

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Key Features:

• Step of registering structural characteristics and load capacity for each of the multiple heterogeneous automated guided vehicles
• Step of registering multiple tasks, including pickup nodes, delivery nodes, and required loads
• Step of setting tasks and initial nodes as vertices for each vehicle and calculating travel costs between vertices
• Configuration for allocating tasks to each vehicle by reflecting primal-dual heuristics and load capacity constraints

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This invention was developed with the support of the National Research Foundation of Korea's Intelligent Growth Autonomous Driving System for Unmanned Vehicles operating safely in congested residential road environments.