Robotic Surface Coverage Using Zoned Mapping and Adaptive Paths
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Solution Overview
Problem
Autonomous cleaning robots face challenges in ensuring full surface coverage of a workspace due to time, compute, and power constraints, with existing methods being inefficient and prone to uneven cleaning and repeat coverage.
Innovation Solution
A robotic system that captures sensor data to create a map of the workspace, segments the map into zones, and optimizes the movement path to cover each zone efficiently, allowing for real-time adjustments and improved surface coverage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If random surface coverage is used, then the robotic device will likely reach all areas of the workspace, but the approach is inefficient and results in uneven cleaning with overlapping serviced areas
Solution Approach 1:
The workspace is divided into discrete cells forming a grid map, allowing the robot to systematically track and manage coverage of each individual cell, preventing overlap and ensuring complete coverage without redundant servicing
2Manufacturing precision
If systematic surface coverage pattern is followed, then even and controlled surface coverage is achieved, but the predetermined pattern is rigid and cannot adapt to different workspace structures, causing repeat coverage or increased coverage time
Solution Approach 1:
The coverage path is dynamically adjusted based on real-time sensor data and workspace characteristics. The robot modifies its movement pattern adaptively rather than following a fixed predetermined path, allowing it to accommodate different workspace layouts while maintaining uniform coverage
Solution Approach 2:
The robot uses sensor feedback to continuously monitor its position and the coverage status of each cell, adjusting its path in real-time to avoid already-covered areas and adapt to workspace obstacles, ensuring both uniformity and adaptability
3Productivity
If complex mapping systems with additional sensors and processors are used, then surface coverage redundancy can be reduced, but acquisition and maintenance costs become prohibitive
Solution Approach 1:
The robot uses its existing sensors and processing capabilities for multiple functions: navigation, obstacle detection, and coverage tracking. The same sensor data is reused to build the grid map and determine coverage status, eliminating the need for additional specialized hardware while maintaining high coverage efficiency
Data Source
AI summary
Some aspects provide a media storing instructions that when executed by a processor of a robot effectuates operations including: capturing first data indicative of a position of the robot relative to objects within the workspace and second data indicative of movement of the robot; generating or updating a map of the workspace based on at least one of: at least a part of the first data and at least a part of the second data; segmenting the map into a plurality of zones; transmitting the map to an application of a communication device; receiving an updated map; generating a movement path based on the map or the updated map; and actuating the robot to traverse the movement path.