Mobile Robot Coverage Planning Around Operational Hazards
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Solution Overview
Problem
Robotic devices face inefficiencies in performing tasks due to operational hazards in work environments, such as obstacles and debris, which can lead to reduced success rates and increased operational challenges.
Innovation Solution
A robotic device generates a coverage plan based on sensor data to prioritize areas with higher likelihoods of successful operations, avoiding areas with operational hazards and debris by creating a map of the environment and using machine learning to optimize navigation routes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If the robotic device operates in areas with operational hazards, then the coverage area is increased, but the operational reliability decreases
Solution Approach 1:
The system performs preliminary mapping and hazard identification before executing the coverage plan. Sensors detect operational hazards and generate a map of the work environment, which is then used to prioritize safe areas. This preliminary action allows the robotic device to plan its coverage path to avoid hazards while still maximizing the covered area.
2Reliability
If the robotic device avoids areas with operational hazards, then the operational reliability is improved, but the coverage area is reduced
Solution Approach 1:
The coverage plan is dynamically adjusted based on real-time sensor data and hazard detection. The system continuously updates the work area map and modifies the coverage path to balance between maximizing coverage and avoiding hazards. This dynamic approach allows the robotic device to adapt its coverage strategy to changing environmental conditions.
3Productivity
If the robotic device uses complex sensor data processing and coverage planning, then the operational efficiency is improved, but the device complexity increases
Solution Approach 1:
The system segments the work environment into discrete areas or zones based on hazard levels and operational success probability. Each area is evaluated independently, and coverage plans are generated for specific segments rather than the entire workspace at once. This segmentation simplifies the processing complexity while maintaining high operational efficiency.
Data Source
AI summary
Provided is a robot-implemented process to create a coverage plan for a work environment, including obtaining, with a robotic device, raw data values of a work environment pertaining to likelihood of operational success and presence or absence of operational hazards contained within the work environment; determining, with one or more processors, the most efficient coverage plan for the robotic device based on the raw data values; and enacting the coverage plan based on the values from the data.