Robotic Surface Coverage Using Zoned Maps to Avoid Repeat Cleaning
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Solution Overview
Problem
Autonomous cleaning robots face challenges in ensuring full workspace coverage due to time, compute, and power constraints, with existing methods being inefficient and prone to redundancy, such as random or systematic surface coverage patterns, and requiring expensive technology for complex mapping systems.
Innovation Solution
A system comprising a robot with sensors and a processor that creates and updates a map of the workspace, segments it into zones, and generates a movement path for efficient coverage, allowing user input for boundary modifications and debris accumulation level adjustments, optimizing surface coverage by minimizing redundancy.
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 given enough time, 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, eliminating random overlapping while ensuring complete coverage
2Manufacturing precision
If systematic surface coverage pattern is followed, then the robotic device provides even and controlled surface coverage, but the predetermined pattern is rigid and cannot adapt to different workspaces, resulting in repeat coverage or increased coverage time
Solution Approach 1:
The coverage path is dynamically generated based on real-time sensor data and workspace characteristics rather than following a fixed predetermined pattern, allowing the robot to adapt to different workspace layouts while maintaining systematic and uniform coverage
Solution Approach 2:
The robot uses sensor feedback to continuously update its understanding of the workspace and adjust its coverage path accordingly, enabling it to adapt to different workspaces while avoiding repeat coverage of already serviced areas
3Productivity
If complex mapping systems with additional sensors, image processors, advanced processors, GPS etc. are used, then surface coverage redundancy can be reduced and efficiency improved, but acquisition and maintenance costs become prohibitive
Solution Approach 1:
The robot uses its existing onboard sensors to perform multiple functions including navigation, mapping, and coverage tracking, eliminating the need for additional expensive sensors and processors while maintaining high coverage efficiency
Data Source
AI summary
Some aspects include a method including: generating, with a processor of the robot, a map of the workspace; segmenting, with the processor of the robot, the map into a plurality of zones; transmitting, with the processor of the robot, the map to an application of a communication device; receiving, with the application, the map; displaying, with the application, the map; receiving, with the application, at least one input for the map; implementing, with the application, the at least one input into the map to generate an updated map of the workspace; transmitting, with the application, the updated map to the processor of the robot; receiving, with the processor of the robot, the updated map; generating, with the processor of the robot, a movement path based on the map or the updated map; and actuating, with the processor of the robot, the robot to traverse the movement path.