Virtual Track Planning for Driverless Transport Vehicles
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Solution Overview
Problem
Conventional driverless transport vehicles are limited by their need to follow physical tracks or markings, making them less flexible in navigating complex environments.
Innovation Solution
A method for planning a virtual lane using a graph-based system that allows driverless transport vehicles to automatically determine and adapt their path based on environmental conditions and vehicle capabilities, enabling flexible movement between a starting point and a destination within an environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional AGVs follow physical tracks or markings on the floor, then the vehicle can reliably navigate the environment, but the flexibility to navigate complex environments is reduced
Solution Approach 1:
The patent replaces physical tracks with a virtual track represented as a graph data structure. The graph contains nodes representing locations and edges representing possible paths, stored in memory as a digital copy of the physical environment layout. This allows the AGV to navigate without physical markings while maintaining reliable path following through software-based virtual tracking.
Solution Approach 2:
The patent substitutes the mechanical detection system (sensors detecting physical tracks or markings) with a computational system that processes graph data. Instead of using cameras or sensors to follow physical lines on the floor, the AGV uses a controller to compute paths based on the virtual graph representation, replacing mechanical track-following with algorithmic path planning.
2Adaptability or versatility
If the driverless transport vehicle stores redundant route information for different paths, then the vehicle can adapt to impassable physical paths, but the device complexity and memory requirements increase
Solution Approach 1:
The graph data structure serves multiple functions simultaneously: it represents the environment layout, encodes all possible paths between locations, stores connectivity information, and enables dynamic path recalculation. A single graph structure replaces the need to store separate route instructions for every possible start-end point combination, providing universal adaptability without redundant storage.
Solution Approach 2:
The path planning system dynamically calculates routes based on current conditions rather than following pre-stored fixed paths. When the AGV encounters an impassable path, the controller can recalculate the route using the graph data structure in real-time, adapting to changing conditions without requiring redundant pre-programmed alternative routes.
Data Source
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AI summary
The invention relates to a driverless transport vehicle (1), a system comprising a computer (10) and a driverless transport vehicle (1), a method for planning a virtual track (B1, B2), and a method for operating a driverless transport vehicle (1). The driverless transport vehicle (1) is intended to move automatically along the virtual track (B1, B2) within an environment (U) from a starting point (SP) to a destination point (ZP), wherein the environment (U) comprises intermediate points (31-35) and the connecting track segments (A) between the intermediate points (31-35), the starting point (SP), and the destination point (ZP). A graph (G) is associated with the environment (U).