Robot Camera Positioning for Higher Visual SLAM Accuracy
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Solution Overview
Problem
Current robot systems face challenges in accurately configuring camera sensors for visual Simultaneous Localization and Mapping (SLAM) due to limitations in camera positioning and orientation, which affects their ability to enhance location estimation accuracy.
Innovation Solution
A method where a robot calculates and selects optimal camera sensor positions and configurations based on SLAM indices, adjusting for factors like camera height, illuminance, and movement speed, using a control unit to reposition or reweight camera images to enhance SLAM performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If camera sensor position is fixed on the robot, then device complexity is reduced, but location estimation accuracy deteriorates
Solution Approach 1:
The patent implements a mounting unit that enables dynamic repositioning of the camera sensor along the robot body. The camera can be moved to different positions (front, rear, left, right, center) based on the robot's movement state, allowing the system to adapt camera placement to optimize location estimation accuracy without requiring multiple fixed cameras throughout the entire robot structure.
Solution Approach 2:
The system changes the positional parameter of the camera sensor dynamically based on robot movement characteristics. When the robot moves forward, the camera is positioned at the front; when moving backward, it shifts to the rear. This parameter change approach allows the same camera hardware to achieve optimal positioning for different operational states, improving location estimation without increasing device complexity.
2Measurement precision
If multiple camera sensors are used, then location estimation accuracy is improved, but device complexity increases
Solution Approach 1:
Instead of using multiple cameras simultaneously, the patent employs a single camera sensor that dynamically repositions itself to different locations on the robot body. This dynamic single-camera approach achieves comparable performance to multiple fixed cameras while significantly reducing device complexity, as only one camera unit and its positioning mechanism are required.
Solution Approach 2:
The single camera sensor serves multiple functions by repositioning to different locations on the robot. It can capture images from front, rear, left, right, and center positions, effectively replacing what would traditionally require multiple dedicated cameras. This multi-functionality reduces the overall camera system complexity while maintaining comprehensive spatial coverage for accurate location estimation.
3Reliability
If camera position is optimized for SLAM, then visual SLAM performance is improved, but ease of operation deteriorates
Solution Approach 1:
The system automatically determines the robot's movement state and autonomously positions the camera sensor to the appropriate location without requiring manual intervention. The control unit receives movement information, calculates the optimal camera position based on SLAM requirements, and actuates the mounting unit accordingly. This self-service approach optimizes visual SLAM performance while maintaining ease of operation, as the camera configuration is handled automatically by the system itself.
Solution Approach 2:
The system implements a feedback loop where the robot's movement state is continuously monitored, and this information feeds back to the camera positioning control. Based on the feedback about current movement (forward, backward, stationary), the camera position is adjusted in real-time to optimize SLAM performance. This closed-loop control ensures reliable visual SLAM while automating the configuration process, eliminating the need for manual camera setup.
Data Source
AI summary
Disclosed herein are a method of configuring a camera position suitable for localization and a robot implementing the same, and the robot according to an embodiment, which configures a camera position suitable for localization, calculates a first SLAM index with respect to an image captured by a first camera sensor on a mounting unit, and calculates a second SLAM index by changing a position of the first camera sensor along the mounting unit, or selects any one of the first SLAM index and the second SLAM index by calculating the second SLAM index with respect to an image captured by a second camera sensor disposed in the mounting unit.