Refuse Can Detection Using Single-Stage Vision for Automated Engagement
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Solution Overview
Problem
Existing refuse collection vehicles lack efficient systems for accurately detecting and engaging refuse cans, leading to inefficiencies in waste collection processes.
Innovation Solution
A refuse detection system utilizing a single-stage object detector, such as RetinaNet, integrated with sensors and actuators on refuse collection vehicles to identify and navigate to refuse cans, enabling precise engagement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional refuse collection vehicles operate without advanced detection systems, then the system complexity remains low, but the accuracy and efficiency of refuse can detection and engagement deteriorates
Solution Approach 1:
The patent replaces manual visual detection and mechanical operation with an automated vision-based detection system using deep learning algorithms (specifically single-stage object detectors like RetinaNet). The system uses image sensors to capture visual data and automatically identifies refuse cans through neural network processing, eliminating the need for operators to manually locate and identify cans, thereby significantly improving detection accuracy while maintaining manageable system complexity through software-based solutions.
Solution Approach 2:
The detection system operates autonomously by automatically capturing images, processing them through the object detector, identifying refuse cans, and generating engagement commands without requiring continuous human intervention. The system serves itself by integrating the detection, identification, and control generation functions into a self-contained automated workflow that reduces dependency on manual operations.
2Productivity
If manual detection and engagement methods are used, then the device complexity is low, but the productivity and efficiency of waste collection deteriorates
Solution Approach 1:
The patent replaces manual detection and engagement operations with an automated control system that uses deep learning-based object detection. The system automatically identifies refuse cans using single-stage detectors and generates precise engagement commands, eliminating manual labor and significantly improving collection efficiency. The automation handles the entire workflow from detection to engagement control without human intervention, transforming a labor-intensive process into an efficient automated operation.
Solution Approach 2:
The system performs preliminary detection and identification of refuse cans before the vehicle reaches them. By using image sensors and object detectors to identify cans in advance, the system can pre-calculate optimal engagement trajectories and prepare control commands, allowing for smoother and more efficient engagement operations when the vehicle arrives at each location.
3Productivity
If automated detection systems are implemented, then the productivity improves, but the use of energy increases
Solution Approach 1:
The patent employs computationally efficient single-stage object detection algorithms (such as RetinaNet) that are optimized for real-time processing on embedded systems. These algorithms process images in a single pass without requiring multiple complex stages, reducing computational load and energy consumption. The system uses image sensors and neural network processors that are designed for low-power operation, enabling automated detection to run efficiently during vehicle operations without excessive energy drain.
4Speed
If single-stage object detectors are used, then the detection speed improves, but the measurement precision may deteriorate compared to multi-stage detectors
Solution Approach 1:
The patent optimizes the single-stage object detector by adjusting key parameters such as anchor box configurations, feature pyramid network depths, and loss function weights to achieve the best balance between speed and accuracy for refuse can detection. The system fine-tunes these parameters specifically for the characteristics of refuse cans in outdoor environments, allowing the single-stage detector to maintain high detection speed while achieving sufficient identification accuracy for practical waste collection operations.
Data Source
AI summary
A system for detecting and engaging a refuse can includes at least one sensor coupled to a refuse collection vehicle and configured to detect objects on one or more sides of the refuse vehicle, an actuator assembly coupled to the refuse collection vehicle and configured to actuate to engage the refuse can, and a controller configured to receive first data from the at least one sensor, input the first data to a single-stage object detector, identify, based on an output of the single-stage object detector, the refuse can, and initiate a control action to move the actuator assembly and the refuse collection vehicle to engage the refuse can.