Autonomous Agricultural Machine Fleet Path Replanning

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Solution Overview

Problem

Current agricultural systems face challenges in achieving precision and reducing soil damage due to the limitations of large-scale equipment, high production costs, and inefficient use of resources, particularly in arable land, which is further exacerbated by the complexity and cost of standalone autonomous agricultural robots.

Innovation Solution

A system comprising a host vehicle and multiple autonomous agricultural machines (AAMs) that use GNSS for location determination and wireless communication, with a control subsystem for dynamic path planning and reallocation in response to operational failures, allowing for continuous agricultural operations without spare AAMs and minimizing soil compaction by reducing the need for detailed on-board sensors and resource carrying capacity.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If large-scale equipment is used for agricultural operations, then productivity is improved, but soil damage increases and manufacturing precision deteriorates

Engineering Contradiction:
Improveagricultural operation efficiencyVSAvoidsoil damage
Core Design Contradiction:
ProductivityVSObject-affected harmful factors

Solution Approach 1:

The system divides the field into multiple zones and uses multiple small autonomous agricultural machines to work simultaneously in different zones. Each machine operates independently with its own GNSS-based navigation, allowing parallel operations that maintain high productivity while each small machine causes minimal soil compaction individually

Inventive Principle:
Principle #1Segmentation

2Extent of automation

If standalone autonomous agricultural machines are used, then automation extent is improved, but device complexity increases and manufacturing cost increases

Engineering Contradiction:
Improveautonomous operation capabilityVSAvoidsystem complexity
Core Design Contradiction:
Extent of automationVSDevice complexity

Solution Approach 1:

The system uses a single central control subsystem that serves multiple autonomous machines, providing path planning, failure detection, and dynamic reallocation functions for the entire fleet. This shared control architecture reduces per-machine complexity while maintaining full automation capability across all units

Inventive Principle:
Principle #6Universality (Multi-functionality)

Solution Approach 2:

The host vehicle acts as an intermediary between the central control subsystem and the autonomous machines, receiving status information from machines and transmitting control commands back to them. This intermediary layer simplifies the communication architecture and reduces the complexity burden on individual machines

Inventive Principle:
Principle #24Intermediary (Mediator)

3Reliability

If spare autonomous agricultural machines are kept for operational failures, then reliability is improved, but productivity deteriorates due to idle machines

Engineering Contradiction:
Improveoperational continuityVSAvoidresource utilization efficiency
Core Design Contradiction:
ReliabilityVSProductivity

Solution Approach 1:

The control subsystem dynamically reallocates field zones among operational machines in real-time based on their status. When a machine fails, the system automatically redistributes its workload to other healthy machines, adapting the operational configuration dynamically without requiring spare machines to remain idle

Inventive Principle:
Principle #15Dynamics

4Measurement precision

If detailed on-board sensors and monitoring systems are installed on AAMs, then measurement precision is improved, but device complexity increases and manufacturing cost increases

Engineering Contradiction:
Improvefailure detection accuracyVSAvoidsensor system complexity
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The system implements feedback by monitoring the actual positions of autonomous machines against their planned paths using GNSS data. The control subsystem detects deviations and infers potential failures from positional anomalies, providing reliable failure detection through simple position-based feedback rather than complex sensor arrays

Inventive Principle:
Principle #23Feedback

Data Source

PatentEP3226674B1Automated agriculture system
Publication Date: 2019.06.12 AGCO INT GMBH
  • EP3226674B1 patent drawingFigure 1
  • EP3226674B1 patent drawingFigure 2
  • EP3226674B1 patent drawingFigure 3A~3B

AI summary

A system for performing an agricultural operation on a field (20), the system including a host vehicle (10), two or more autonomous agricultural machines (12A –12F) configured for performing the said agricultural operation; and a control subsystem (14) for path planning and controlling the movement of each autonomous agricultural machine relative to the host vehicle in the performance of the agricultural operation. The control subsystem (14) is configured to dynamically re-plan the movement of one or more of the autonomous agricultural machines (12A –12D, 12F) in response to a detected failure of an autonomous agricultural machine (12E) as indicated by its position relative to its planned path.