Observer Robot Relocation for Accurate Target Tracking
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Solution Overview
Problem
In dynamic construction sites, observer robots may lose line of sight or fail to provide position information at desired accuracy due to occlusions or changes in requirements, necessitating adaptive relocation to maintain accurate tracking of target objects.
Innovation Solution
A control system that detects such events and optimizes observer robot locations by determining capable sensor positions and intended positional accuracy levels, selecting new locations to ensure unobstructed lines of sight and desired accuracy for priority targets, and directing robots to relocate accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If observer robots are relocated to maintain line of sight and positional accuracy, then measurement precision and reliability are improved, but device complexity and operational complexity increase
Solution Approach 1:
The system dynamically relocates observer robots based on real-time occlusion detection and positional accuracy requirements. The control system continuously monitors sensor data and automatically commands robot relocation when measurement quality degrades, transforming a static observation system into an adaptive dynamic one that maintains optimal measurement conditions without manual intervention
Solution Approach 2:
The system implements closed-loop feedback by monitoring sensor occlusion status and positional accuracy metrics, then using this information to trigger automated relocation decisions. The control system receives feedback from sensors about measurement quality and responds by adjusting observer robot positions, creating a self-correcting system that maintains measurement precision
2Measurement precision
If multiple observer robots are deployed to track priority target objects, then measurement precision and coverage are improved, but device complexity and coordination difficulty increase
Solution Approach 1:
Each observer robot operates autonomously with its own sensors and control capabilities, making independent relocation decisions based on local occlusion detection. The robots self-manage their positioning to maintain measurement quality without requiring complex centralized coordination, reducing system complexity while maintaining measurement precision
Solution Approach 2:
The system divides the worksite into multiple observation zones, with each observer robot responsible for specific target objects or regions. This segmentation allows independent optimization of each robot's position and function, simplifying coordination while improving overall measurement coverage and precision across the entire worksite
Data Source
AI summary
Example implementations may relate to optimization of observer robot locations. In particular, a control system may detect an event that indicates desired relocation of observer robots within a worksite. Each such observer robot may have respective sensor(s) configured to provide information related to respective positions of a plurality of target objects within the worksite. Responsively, the control system may (i) determine observer robot locations within the worksite at which one or more of the respective sensors are each capable of providing information related to respective positions of one or more of the plurality of target objects and (ii) determine a respectively intended level of positional accuracy for at least two respective target objects. Based on the respectively intended levels of positional accuracy, the control system may select one or more of the observer robot locations and may direct one or more observer robots to relocate to the selected locations.