Visual Servoing Path Planning for Camera Occlusion Avoidance
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Solution Overview
Problem
Existing visual servoing systems face challenges in maintaining camera line of sight to targets due to self-occlusions and environmental obstacles, leading to ineffective control of robotic arms in dynamic environments.
Innovation Solution
Employing multiple cameras on a robotic arm, utilizing redundant manipulators to maintain target visibility through path planning algorithms that account for environmental and self-occlusions, and integrating kinematic and dynamic optimization to ensure continuous feedback control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a single camera is used on the robotic arm, then the device complexity is reduced, but the target visibility is lost due to self-occlusions and environmental obstacles
Solution Approach 1:
The camera system is segmented into multiple cameras positioned at different locations on the robotic arm. Each camera provides a different field of view, allowing the system to maintain target visibility from multiple angles and avoid self-occlusions that would affect a single camera.
Solution Approach 2:
The system transitions from a single-point camera view to multi-point spatial distribution of cameras along the robotic arm. This dimensional expansion in the spatial arrangement of cameras enables continuous target tracking by selecting appropriate cameras based on their positional advantages relative to the target and occlusion sources.
2Reliability
If multiple cameras are deployed on the robotic arm, then continuous target visibility is achieved, but the device complexity increases
Solution Approach 1:
The camera selection is made dynamic through real-time evaluation of target visibility conditions. The system continuously assesses which camera provides the best view of the target and dynamically switches between cameras based on current occlusion conditions, robotic arm configuration, and target position, rather than using a fixed camera assignment.
Solution Approach 2:
The system changes operational parameters by selecting different active cameras based on quantitative evaluation of visibility metrics. The camera selection depends on parameters such as occlusion level, field of view coverage, and geometric relationships between camera positions, target, and robotic arm configuration.
3Reliability
If path planning is optimized for camera visibility, then target tracking reliability improves, but the computational complexity increases
Solution Approach 1:
The system performs preliminary evaluation of camera visibility conditions during path planning. By assessing which cameras will maintain target visibility along planned trajectories and pre-computing optimal camera selections, the system avoids complex real-time optimization during execution, reducing computational burden while maintaining tracking reliability.
4Adaptability or versatility
If redundant manipulators are used to maintain visibility, then the adaptability to avoid occlusions improves, but the device complexity increases
Solution Approach 1:
The robotic arm's redundant degrees of freedom serve multiple functions: they enable both the primary task of manipulating the end effector and the secondary function of maintaining camera visibility. By coordinating these redundant movements with camera selection, the system achieves occlusion avoidance without adding dedicated visibility-maintenance mechanisms, thus avoiding increased device complexity.
Data Source
AI summary
Various aspects of techniques, systems, and use cases may be used for camera and end-effector planning for visual servoing for example in redundant manipulators. A technique may include generating a set of paths of an end effector of a robotic arm, and ranking the set of paths using an objective function that results in an improvement to a distance between the end effector and a target while maintaining a collision mitigation path for the end effector and minimizing occlusion of a camera affixed to a joint of the robotic arm. The technique may include converting a path of the set of paths into a trajectory based on the ranking, and outputting the trajectory for controlling the robotic arm to move the end effector.