Modular Farm Robot Control for Multi-Task Autonomous Field Work
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Solution Overview
Problem
Current technologies face challenges in effectively reducing weeds, controlling pests, harvesting crops, and performing daily farm tasks efficiently and economically, with existing methods being limited in scope and often leading to herbicide resistance, soil disturbance, and manual labor requirements.
Innovation Solution
A system of autonomous, cooperative robots using renewable energy sources, modular components, and human-assisted machine learning to perform tasks such as weed suppression, pest control, and crop harvesting, with cooperative robots assisting each other and a control company managing deployment, maintenance, and data collection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a robotic system is designed to perform multiple agricultural tasks autonomously, then task versatility and productivity are improved, but device complexity and difficulty of detecting and measuring increase
Solution Approach 1:
The robotic system is divided into modular functional units including a mobile platform, interchangeable payloads (weed suppression attachment, pest control attachment, cargo transport attachment), and sensor systems. Each module can be independently attached or detached, allowing the base robot to perform multiple tasks by swapping attachments rather than integrating all functions into a single complex unit.
Solution Approach 2:
The mobile robot platform is designed with universal interfaces and mounting mechanisms that allow a single base unit to support multiple different payloads and attachments. The robot includes standardized receiver components that can accommodate various task-specific attachments, enabling one robot to perform weed control, pest management, cargo transport, and monitoring functions through attachment interchangeability.
2Productivity
If autonomous operation is implemented in unstructured environments, then productivity and reduction of human intervention are improved, but reliability and difficulty of detecting and measuring worsen
Solution Approach 1:
The robot is pre-equipped with multiple sensor types (cameras, LIDAR, proximity sensors, environmental sensors) and pre-programmed navigation algorithms that enable it to autonomously detect, map, and navigate unstructured environments before performing tasks. The system includes pre-trained machine learning models for object recognition and path planning that allow reliable autonomous operation without human intervention in previously unmapped areas.
Solution Approach 2:
The autonomous robot incorporates continuous feedback loops through onboard sensors that monitor its position, orientation, task execution status, and environmental conditions. The sensor system provides real-time data to the control system, which adjusts navigation and task performance dynamically. Feedback from cameras and proximity sensors allows the robot to detect obstacles and adjust its path autonomously, maintaining reliability in unstructured environments through continuous environmental awareness and adaptive response.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system enables efficient, cost-effective, and environmentally friendly performance of farm tasks, reducing manual labor and herbicide use, while ensuring robot reliability through modular design and cooperative functionality.
Implementation Method 1
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Data Source
AI summary
This invention is a system to control depredators and predators having a configurable ground utility robot where the robot has an all-terrain autonomous mobile apparatus that can navigate in both structured and unstructured environments, a processor, at least one sensor that communicates with the processor, and at least one computer program that performs at least the following functions: receives and interprets data from the at least one sensor; controls the mobile apparatus; at least one control device; and where the ground utility robot is powered by renewable energy.