Robot Mapping Deployment Based on Interest and Added Cost
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Solution Overview
Problem
Autonomous and semi-autonomous robots deployed in inadequately mapped environments face stale map data issues, particularly in dynamic areas, where existing methods like SLAM may not efficiently prioritize mapping tasks alongside primary tasks without considering costs and interest levels.
Innovation Solution
A method that determines the measure of interest in mapping an area and calculates the added cost for robots to perform mapping tasks while executing primary tasks, selectively deploying robots to divert from shortest paths and allocate resources based on justified interest and cost analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a robot diverts from the shortest path to map an area of interest, then the map data quality is improved, but the task completion time increases
Solution Approach 1:
The robot performs mapping in a selective manner by diverting only to areas of heightened interest rather than mapping the entire environment. The system calculates an added cost metric to determine whether the benefit of improved map data quality justifies the time penalty, implementing partial mapping action only where necessary.
2Area of stationary object
If multiple robots are deployed to perform mapping, then the coverage area increases, but the resource allocation complexity increases
Solution Approach 1:
The system changes the parameter of robot selection by introducing a cost-benefit metric that quantifies the added cost of mapping versus the interest level. This parameter transformation converts a complex multi-robot coordination problem into a calculable optimization problem where the robot with the lowest added cost is selected.
3Productivity
If a robot performs both primary tasks and mapping simultaneously, then the productivity is improved, but the task execution reliability decreases
Solution Approach 1:
The system implements dynamic task allocation where the robot's path and activities are adjusted in real-time based on the calculated added cost metric. The robot can dynamically switch between primary task execution and mapping activities, with the ability to adapt its behavior based on changing environmental conditions and task priorities.
Data Source
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AI summary
Methods, apparatus, systems, and computer-readable media are provided for selectively deploying robots to performing mapping based on added cost. In various implementations, a measure of interest in mapping an area of an environment may be determined. A cost associated with a robot performing a task may also be determined. Then, an added cost associated with the robot mapping the area of the environment while performing the task may be determined. The robot may be selectively deployed to map the area while performing the task in response to a determination that the measure of interest justifies the added cost.