Robot Sensor Layout for Occlusion-Aware Motion Planning
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Solution Overview
Problem
Existing motion planning systems face challenges in generating efficient, robust, and computationally efficient motion plans for robots operating in shared workspaces, particularly due to occlusions caused by robots and obstacles, which increase computational resources and collision risks.
Innovation Solution
Optimize the layout of sensors and their positions/orientations in the operational environment to minimize occlusions, using a layout optimizer system that considers robot poses, transitions, and environmental knowledge to enhance sensor coverage and reduce occlusions, thereby improving motion planning efficiency and robustness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If sensors are placed to cover more space, then sensor coverage is improved, but occlusions by robots and obstacles increase
Solution Approach 1:
The system transitions from 2D sensor placement to 3D spatial optimization, considering robot poses and transitions in three-dimensional space. By optimizing sensor positions and orientations across multiple dimensions, the system achieves comprehensive coverage while minimizing occlusions from robots moving through various poses.
Solution Approach 2:
The layout optimization is performed in advance before robot operations begin. The system pre-calculates optimal sensor placements by simulating robot poses and transitions, ensuring that sensors are positioned to minimize occlusions throughout the entire operational sequence before any actual robot movement occurs.
2Reliability
If occlusions are treated as occupied space to prevent collisions, then collision safety is improved, but motion planning difficulty increases
Solution Approach 1:
The system dynamically distinguishes between actual occupied space and occluded space. Rather than treating all occluded regions as permanently occupied, the motion planner uses real-time sensor data to differentiate between space blocked by static obstacles versus space temporarily obscured by robots, enabling more flexible and efficient path planning while maintaining safety.
Solution Approach 2:
The system implements continuous feedback loops where sensors monitor the operational environment in real-time, providing updated information about robot positions and environmental obstacles. This feedback enables the motion planner to adjust its understanding of occupied versus occluded space dynamically, reducing unnecessary constraints and simplifying motion planning while maintaining collision safety.
Data Source
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AI summary
A layout of a robotic operational environment is optimized to at least reduce or minimize occlusion of one or more sensors, to improve computational efficiency of motion planning, and/or improve an efficiency and/or robustness of generated motions plans. A respective sensor pose (i.e., positioned and oriented) for one or more sensors may be determined while taking into account the various robot poses of the robot(s) and transitions between robot poses. For instance, cost values that represent occlusion may be determined, and candidate sensor poses evaluated based on cost values or aggregated cost. The total number of sensors to be employed may not be known before execution, and in fact may be determined only after several iterations, upon reaching a termination condition (e.g., task completion time). Sensors make take any variety of forms, e.g., digital camera, radar, LIDAR, sonar, passive infrared (PIR) motion detector.