Multi-Perspective Item Feature Detection for Robotic Tracking
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Solution Overview
Problem
Robotic equipment in manufacturing environments faces challenges in identifying and tracking items due to variations in part positioning and changing lighting conditions, leading to increased costs and delays.
Innovation Solution
A system and method for detecting and tracking item features by capturing images from multiple perspectives, identifying edges and corners, and marking them as features to be tracked, with the ability to adjust lighting conditions programmatically to maintain detection accuracy across varying environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If robotic equipment is used to perform repetitive tasks with precision, then productivity and cost-effectiveness are improved, but the ability to identify and position parts varies due to part variations and positioning challenges
Solution Approach 1:
The system performs preliminary detection and tracking of part features (edges, corners, contours) before the robotic equipment processes the part. By pre-identifying part positions and characteristics using image capture from multiple perspectives, the system prepares positioning information in advance, allowing the robotic equipment to operate at high speed without sacrificing identification accuracy.
Solution Approach 2:
The patent introduces an intermediary detection system consisting of image capture modules, processors, and feature tracking algorithms that mediate between the part and the robotic equipment. This intermediary system extracts and tracks key geometric features (edges, corners, contours) to provide reliable positioning information, bridging the gap between part variations and robotic precision requirements.
2Manufacturing precision
If special positioning mechanisms are installed for each robotic equipment station, then part positioning precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent replaces complex mechanical positioning mechanisms with an optical detection and image processing system. Instead of using physical positioning devices at each robotic station, the system captures images, detects geometric features (edges, corners, contours), and computationally determines part positions, thereby eliminating the need for mechanical positioning hardware while maintaining precision.
Solution Approach 2:
The system creates a digital copy or representation of the part's geometric features through image capture and processing. By detecting and tracking key points (edges, corners, contours) in the image space, the system establishes a virtual model of part position and orientation that guides the robotic equipment, replacing the need for physical positioning mechanisms.
3Difficulty of detecting and measuring
If detection methods are used to identify items based on features, then part identification capability is improved, but reliability deteriorates due to changing lighting conditions and environmental variations
Solution Approach 1:
The system dynamically adapts to changing environmental conditions by continuously tracking geometric features (edges, corners, contours) across multiple images and perspectives. The feature tracking algorithms adjust to lighting variations and environmental changes by maintaining consistency in detecting invariant geometric properties, allowing reliable detection despite dynamic environmental factors.
Solution Approach 2:
The patent moves from single-perspective detection to multi-perspective detection by capturing images from multiple angles and viewpoints. By analyzing geometric features across multiple dimensions and perspectives, the system identifies consistent invariant features that remain detectable regardless of lighting conditions or environmental variations, thereby improving detection reliability.
Data Source
AI summary
Technologies are generally described for detection and tracking of item features. In some examples, features of an object may be initially found through detection of one or more edges and one or more corners of the object from a first perspective. In addition, determination may be made whether the detected edges and corners of the object are also detectable from one or more other perspectives. In response to an affirmative determination, the detected edges and of the object may be marked as features to be tracked, for example, in subsequent frames of a camera feed. The perspectives may correspond to distributed locations in a substantially umbrella-shaped formation centered over the object. In other examples, lighting conditions of an environment where the object is being tracked may be programmatically controlled.