Mobile Robot Coverage Planning With Hazard-Aware Mapping
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Solution Overview
Problem
Existing robotic devices lack efficiency in identifying and navigating around operational hazards in work environments, leading to unsatisfactory performance and potential damage.
Innovation Solution
Robotic devices equipped with sensors and processors generate a coverage plan that prioritizes areas with low operational hazards, adjusting navigation based on sensor data and historical encounters to optimize work efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If robotic devices use traditional random or systematic cleaning patterns, then coverage is achieved, but operational efficiency decreases due to repeated encounters with hazards and unnecessary traversal of already-cleaned areas
Solution Approach 1:
The robotic device performs preliminary mapping and hazard identification before executing the cleaning task. The processor creates a detailed map of the environment including locations of hazards and previously cleaned areas, then uses this pre-acquired information to plan an optimized cleaning path that avoids hazards and redundant areas from the outset
Solution Approach 2:
The system continuously updates its internal map based on sensor feedback during operation. As the robot encounters hazards or cleans areas, this information is fed back to the processor which dynamically adjusts the cleaning path in real-time, improving both efficiency and operational reliability through adaptive decision-making
2Ease of operation
If robotic devices navigate without hazard awareness, then movement is simple, but device damage increases due to collisions with obstacles
Solution Approach 1:
The robotic device performs preliminary environmental scanning and hazard mapping before navigation. Sensors detect obstacles and hazards in advance, and the processor creates a hazard-aware map that guides navigation, allowing the robot to plan safe paths rather than reacting to obstacles during movement
Solution Approach 2:
The processor acts as an intermediary between the navigation system and the physical environment. It processes sensor data about hazards and translates this information into safe navigation commands, mediating between the simple movement capability and the complex hazardous environment
3Manufacturing precision
If robotic devices clean all areas uniformly, then complete coverage is achieved, but time consumption increases due to revisiting hazard-prone or already-cleaned areas
Solution Approach 1:
The cleaning system applies different strategies to different areas based on local characteristics. Hazard-prone areas are avoided or given reduced priority, while safe areas are cleaned thoroughly. The processor assigns different weights or priorities to different regions of the environment based on hazard levels and cleaning status
Solution Approach 2:
The system performs preliminary hazard assessment and area classification before cleaning. By pre-identifying which areas are safe and which are hazardous, the robot can plan an efficient cleaning sequence that ensures complete coverage of necessary areas while minimizing time spent in hazard-prone zones
Data Source
AI summary
A method for covering a work environment by a robot, including: obtaining sensor data indicative of operational hazards; generating a map based on data obtained from sensors of the robot; determining an object type of an operational hazard based on extracted features and a database of various object types and their features; generating a coverage plan for areas of the work environment; executing the coverage plan by the robot; capturing debris sensor data indicative of at least presence and absence of debris in locations within the work environment; determining areas of the work environment with a high presence of debris and a low presence of debris, wherein the map is updated to distinguish the areas with the high presence of debris and the areas with the low presence of debris.