Industrial Vehicle Fleet Control for Distributed Payload Allocation
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Solution Overview
Problem
As the number of industrial vehicles increases and tasks become more complex, the computational power required to determine the most suitable vehicle for each subtask grows exponentially, leading to increased bandwidth and communication signal demands, necessitating a reduction in complexity, bandwidth requirements, and signal handling in systems controlling industrial vehicles for payload movement.
Innovation Solution
An industrial vehicle with a control unit that obtains vehicle and payload information, determines the most suitable vehicle based on optimization criteria, and provides instructions for payload movement, eliminating the need for a central control unit by enabling vehicles to communicate and determine instructions among themselves.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a central control unit is used to control industrial vehicles, then coordination and control capability are improved, but system complexity and computational power requirements increase exponentially
Solution Approach 1:
The patent segments the centralized control function into distributed control units, where each industrial vehicle has its own control unit that can independently make decisions. This divides the monolithic central control system into multiple autonomous agents, reducing overall system complexity while maintaining coordination capability through peer-to-peer communication.
Solution Approach 2:
Each industrial vehicle's control unit is empowered to independently determine its own tasks and make decisions without constant central direction. The vehicles perform self-service by autonomously assessing their own capabilities, selecting appropriate tasks from the task list, and executing them based on local optimization criteria, thereby reducing the computational burden on any single control entity.
2Productivity
If fleet size and operating area increase, then payload movement capability is improved, but bandwidth and communication signal requirements increase
Solution Approach 1:
The communication architecture is segmented into localized peer-to-peer interactions rather than centralized hub-and-spoke communication. Each vehicle communicates only with relevant nearby vehicles and the task management system as needed, dividing the communication load into smaller, manageable segments that scale better with fleet size and area.
Solution Approach 2:
Vehicles perform partial communication actions by exchanging only necessary task-related information with nearby vehicles rather than maintaining constant full-state communication with all fleet members. This reduces bandwidth consumption while still enabling coordinated payload movement across larger areas through selective, event-driven communication.
3Reliability
If central control unit determines task allocation, then task coordination is improved, but computational power requirements grow exponentially
Solution Approach 1:
The task allocation computation is segmented and distributed across multiple vehicle control units rather than centralized in one powerful computer. Each control unit independently evaluates tasks based on its own capabilities and local conditions, dividing the exponential computational problem into multiple manageable polynomial-time decisions made in parallel by different vehicles.
Solution Approach 2:
Each vehicle's control unit independently determines its own task assignments by evaluating the task list against its capabilities and current state. This self-service approach eliminates the need for a single high-power central computer to solve complex optimization problems, distributing computational load across many lower-power individual units.
Data Source
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AI summary
The disclosure relates to an industrial vehicle (100, 200, 300, 400) for optimisation of moving payload (10) from a first position (A) to a second position (B). The industrial vehicle comprises: control unit (110, 210, 310, 410) for controlling the industrial vehicle and carrying means (120, 220, 320, 420) for carrying a payload, wherein the control unit is connected to the carrying means. The control unit being configured to: obtain vehicle information of at least one industrial vehicle, said vehicle information comprising position data of at least one industrial vehicle; obtain payload information of a payload, said payload information comprising position data of the payload; obtain optimisation criteria comprising at least time required until the payload has been moved from the first position to the second position; determine, based on the obtained vehicle information, the obtained payload information and the obtained optimisation criteria, at least one selected industrial vehicle, of the at least one industrial vehicle, to move the payload; and provide, to the at least one selected industrial vehicle, an instruction to move the payload. Further, the disclosure relates to a method for optimisation of moving payload from a first position (A) to a second position (B). Yet further, the disclosure relates to a computer program carrying out the method, a computer-readable medium carrying out the method, and a system for optimisation of moving payload comprising a plurality of the industrial vehicles.