Work Machine Control Using Camera-Based Object Detection
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Solution Overview
Problem
Existing work machine automatic control systems do not adequately consider the peripheral environment, leading to potential safety hazards and inefficiencies in operations.
Innovation Solution
A control system that includes a camera and processor for image analysis using an object detection model to identify specific objects and their distances, allowing the work machine to perform tasks automatically while accounting for its surroundings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automatic control is implemented without environmental awareness, then productivity is improved, but safety and reliability deteriorate
Solution Approach 1:
The system continuously captures images of the peripheral environment using a camera and feeds this visual information back to the controller. The controller analyzes the images to detect objects, people, and environmental features, then adjusts the automatic operation based on this feedback. This closed-loop feedback mechanism enables the work machine to maintain high productivity while adapting to real-time environmental conditions, thereby ensuring operational safety.
Solution Approach 2:
An image processing unit acts as an intermediary between the camera and the controller. This intermediary component analyzes captured images, detects objects and distances, and translates visual information into control instructions. By introducing this intermediate processing layer, the system can autonomously interpret environmental data and make informed decisions, resolving the contradiction between automated operation and environmental awareness.
2Reliability
If image analysis is performed to detect objects and distances, then reliability is improved, but device complexity increases
Solution Approach 1:
The system replaces complex mechanical sensing arrangements with a camera-based optical system. Instead of using multiple specialized sensors (ultrasonic, laser, radar) that would increase hardware complexity, a single camera captures comprehensive environmental data. The image processing unit then analyzes this visual data to extract object information and distances, achieving reliable environmental awareness with simpler device architecture.
Solution Approach 2:
The camera serves multiple functions: it captures images for environmental awareness, provides data for object detection, enables distance measurement, and supports safety monitoring. By making the camera a multi-functional component, the system avoids adding separate specialized sensors for each function, thereby improving reliability without proportionally increasing device complexity.
Data Source
AI summary
A system includes a work machine, a camera, and a processor. The camera captures an image including a periphery of the work machine. A processor acquires image data indicative of a captured image captured by a camera. The processor acquires, from image data, a specific object present within the captured image and a distance from the work machine to the specific object by performing image analysis using an object detection model. The object detection model is trained an image of the specific object and the distance to the specific object. The processor controls the work machine based on the distance from the work machine to the specific object when the specific object is detected in the captured image.