Event-Based Light Sensor Servo Control for Robot Motion Tracking
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Solution Overview
Problem
Current servo control systems for robots, especially in high-speed manufacturing environments, face challenges with accuracy and cost due to the need for expensive mechanical sensors and high-frame rate cameras, which are prone to motion blur and difficult light conditions, requiring significant computational power.
Innovation Solution
The use of event-based light sensors to detect and process motion characteristics of robots and objects, reducing computational power requirements and improving performance in challenging light conditions, with optional integration of frame-based cameras for additional visual understanding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-frame rate cameras are used to improve tracking accuracy, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent replaces frame-based camera systems with event-based light sensors that operate asynchronously. Instead of capturing complete frames at high frame rates, the event-based sensor detects only changes in light intensity, generating events only when motion occurs. This substitution reduces device complexity while maintaining measurement precision for moving objects, as the event-based approach naturally filters out static scene information and focuses computational resources on dynamic elements.
Solution Approach 2:
The patent changes the fundamental operating parameter of the sensing system from fixed-frame-rate capture to event-driven asynchronous sampling. By switching from a time-based sampling mechanism (frame rate) to an event-based sampling mechanism triggered by light intensity changes, the system achieves high measurement precision for moving objects without requiring high frame rates, thereby reducing device complexity and computational requirements.
2Measurement precision
If high-frame rate cameras are used to reduce motion blur, then measurement precision is improved, but use of energy increases
Solution Approach 1:
The patent replaces the energy-intensive frame-based camera system with an event-based light sensor system. The event-based approach processes only changed pixels in the scene, generating events asynchronously when light intensity changes exceed a threshold. This substitution dramatically reduces computational power requirements and energy consumption while maintaining motion capture accuracy, as the system processes only relevant dynamic information rather than entire frames at high rates.
Solution Approach 2:
The patent applies partial action by processing only the necessary portion of visual information - specifically, only the pixels that have changed in the scene. Instead of processing complete frames at high frame rates, the event-based system generates events only for pixels experiencing light intensity changes. This selective processing reduces energy consumption and computational power while maintaining measurement precision for moving objects, as static portions of the scene are ignored.
3Measurement precision
If expensive mechanical sensors are used to improve position regulation accuracy, then measurement precision is improved, but cost increases
Solution Approach 1:
The patent replaces mechanical sensors with event-based light sensors for position regulation. Instead of using mechanical encoders or resolvers mounted on robot joints, the system uses vision-based event detection to track the robot's end effector and the object. This substitution eliminates complex mechanical sensing systems while achieving comparable or superior position regulation accuracy through optical measurement of motion characteristics.
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
This approach provides high dynamic range, reduced motion blur, and lower data rates, enabling efficient and accurate servo control with lower costs, while maintaining high productivity and adaptability to uncertainties.
Implementation Method 1
receiving events from at least one event-based light sensor, depending on variations of incident light from a workspace including the robot and the object
Data Source
Figure 1~2
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Figure 5~6
AI summary
The servo control method for controlling movement of a robot (2) with respect to an object (A) with which the robot interacts, comprises receiving events from at least one event-based light sensor (10), depending on the variation of incident light from a workspace including the robot and the object, processing the events to extract motion characteristics of the robot and/or the object, and adjusting the movement of the robot according to the extracted motion characteristics.