Robot End-Effector Identification Using 3D Vision Models
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current proximity sensors in industrial environments, such as inductive and optical sensors, are limited by their one-dimensional nature, prone to fouling, and misalignment, which complicates accurate detection of workpiece position and end effector identity, leading to potential safety hazards and productivity losses.
Innovation Solution
A system that uses sensors to record images of end effectors and compares them to digital models, generating 3D spatial or voxel-grid representations to identify and confirm the presence and type of end effectors, even in arbitrary orientations, thereby enhancing safety and productivity by accurately determining the end effector's identity and position.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple proximity sensors are used to detect workpiece position and end effector identity, then detection coverage is improved, but device complexity and susceptibility to fouling increase
Solution Approach 1:
The patent combines multiple sensing functions (position detection, identity recognition, orientation detection) into a single camera-based vision system. Instead of using separate proximity sensors for each function, the system uses image capture and processing to achieve all detection goals simultaneously, reducing the number of components and overall system complexity.
Solution Approach 2:
The patent replaces mechanical/electromagnetic proximity sensors with an optical vision system. The camera-based system captures images and uses computer vision algorithms to detect workpiece position, identify end effectors, and determine orientations, substituting the traditional electromagnetic field-based proximity sensing approach with optical imaging and digital processing.
2Measurement precision
If proximity sensors are placed close to the manufacturing process for accurate detection, then measurement precision is improved, but susceptibility to fouling and misalignment increases
Solution Approach 1:
The patent introduces an intermediary optical path (camera lens and imaging system) between the sensor and the target objects. This allows the sensing system to operate from a distance while maintaining detection accuracy, as the camera can capture images of end effectors and workpieces without being in direct contact with the manufacturing process environment where fouling occurs.
3Reliability
If conservative safety zones are assumed based on largest end effector dimensions, then safety is ensured, but productivity is reduced due to unnecessary restrictions
Solution Approach 1:
The patent implements a feedback mechanism where the vision system continuously identifies the actual end effector attached to the robot and communicates this information to the safety system. This real-time feedback allows the safety system to adjust protective separation distances dynamically based on the actual end effector dimensions rather than assuming the maximum size, thereby maintaining safety while improving productivity.
Data Source
AI summary
Systems and methods for identifying a robot end effector in a processing environment may utilize one or more sensors for digitally recording visual information and providing that information to an industrial workflow. The sensor(s) may be positioned to record at least one image of the robot including the end effector. A processor may determine the identity of the end effector from the recorded image(s) and a library or database stored digital models.