Active Robotic Vision Coordination for Single-Camera Object Tracking
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Solution Overview
Problem
Conventional robotic control systems face issues with system lag, increased costs, and inaccuracies due to the use of multiple sensors, and lack human-like hand-eye coordination, as they rely on fixed cameras with limited field of view and require multiple cameras for accurate object tracking.
Innovation Solution
A robotic control system that uses a dynamically adjustable imaging system with a gimbal-mounted camera and a processor to actively track objects, allowing for real-time adjustments of the imaging device and robot to maintain focus on a region of interest, enabling human-like hand-eye coordination and reducing the need for multiple sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sensors are used for robotic control, then measurement precision and reliability are improved, but device complexity and system cost increase
Solution Approach 1:
The patent combines multiple sensing functions (depth sensing, color imaging, motion tracking) into a single integrated camera system. The camera incorporates both depth sensor and color sensor capabilities, eliminating the need for separate sensors while maintaining measurement precision and reducing system complexity.
Solution Approach 2:
The camera system is designed to perform multiple functions simultaneously: depth measurement, color capture, object tracking, and motion detection. This multi-functional approach replaces multiple specialized sensors with a single universal imaging device that achieves the same control accuracy.
2Area of stationary object
If multiple fixed cameras are positioned at different viewing angles, then the field of view and object tracking capability are improved, but device complexity and system cost increase
Solution Approach 1:
The patent employs a movable camera system that can dynamically adjust its viewing angle and position to track objects throughout the workspace. Instead of using multiple fixed cameras, a single camera moves adaptively to maintain optimal viewing angles, providing comprehensive coverage while reducing system complexity.
Solution Approach 2:
The camera system adds temporal and spatial dynamics by moving the camera through three-dimensional space and adjusting viewing angles in real-time. This transforms a static multi-camera arrangement into a dynamic single-camera system that achieves the same field of view coverage through motion rather than multiplication of components.
3Ease of manufacture
If conventional fixed cameras are used, then system implementation is simplified, but the field of view is limited and adaptability decreases
Solution Approach 1:
The camera system incorporates movable mounting mechanisms that allow real-time adjustment of camera position and orientation. This dynamic capability enables the system to adapt to different objects, tasks, and workspace configurations while maintaining relatively simple implementation through standardized mechanical components.
4Productivity
If real-time object tracking is implemented, then productivity and response time are improved, but processing requirements and system complexity increase
Solution Approach 1:
The patent merges the vision processing and robot control functions into an integrated system where the camera directly provides tracking data to the robot controller. This unified approach reduces the complexity of coordination between separate systems while enabling real-time tracking and response.
Solution Approach 2:
The system implements continuous feedback loops where the camera tracks the object's position and motion, and this information is immediately used to adjust robot movements. This closed-loop control enables real-time adaptability and high productivity through straightforward feedback mechanisms rather than complex predictive models.
Data Source
AI summary
The present disclosure generally relates to a robotic control system and method that utilizes active perception to gather the relevant information related to a robot, a robotic environment, and objects within the environment, and allows the robot to focus computational resources where needed, such as for manipulating an object. The present disclosure also enables viewing and analyzing objects from different distances and viewpoints, providing a rich visual experience from which the robot can learn abstract representations of the environment. Inspired by the primate visual-motor system, the present disclosure leverages the benefits of active perception to accomplish manipulation tasks using human-like hand-eye coordination.