Robotic Coverage Path Planning for Obstacle-Adaptive Cleaning
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Solution Overview
Problem
Autonomous cleaning robots face challenges in ensuring full coverage of a workspace in a timely manner due to inefficiencies in navigation and path planning, with existing solutions being either expensive or impractical for consumer use.
Innovation Solution
The implementation of a set of cost-effective methods and movement patterns for autonomous robotic devices to establish working zones, detect obstacles, and plan collision-free paths using electronic computing devices, including triangle, daisy, asterisk, closest obstacle, and farthest obstacle path modes to optimize workspace coverage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If random movement patterns are used for navigation, then the robot can operate with simple algorithms and lower cost, but the cleaning efficiency approaches zero as time approaches infinity due to excessive path overlap
Solution Approach 1:
The robot performs preliminary mapping of the workspace environment before cleaning operations. By预先 establishing a map of the area using sensors (ultrasonic, infrared, or camera-based), the robot knows the boundaries and obstacles in advance, allowing it to plan efficient cleaning paths without random movement and excessive overlap
Solution Approach 2:
The robot continuously tracks its own position and the areas it has already cleaned using feedback from sensors and onboard processors. This feedback mechanism allows the robot to adjust its path in real-time to avoid already-cleaned areas and maintain high cleaning efficiency throughout the workspace
2Measurement precision
If sophisticated navigation technologies like differential GPS, ultrasonic transducers, or rotating laser rangefinders are used, then the robot can achieve better localization and path determination, but the system becomes more expensive and mechanically complex
Solution Approach 1:
The patent employs fixed electronic sensors (ultrasonic transducers, infrared sensors, or camera systems) that serve multiple functions: they detect obstacles, map the workspace boundaries, and determine the robot's position relative to those boundaries. This multi-functional approach eliminates the need for specialized mechanical devices like rotating laser rangefinders while achieving comparable localization accuracy
Solution Approach 2:
The invention replaces mechanical navigation systems (rotating laser rangefinders, physical bar code targets) with fixed electronic sensing systems. The electronic sensors and computational algorithms provide the necessary localization and mapping capabilities without the mechanical complexity, moving parts, and high costs associated with traditional mechanical navigation devices
3Measurement precision
If bar code targets are used for navigation, then the robot can achieve precise positioning, but the robot must see at least four bar codes simultaneously which creates operational problems
Solution Approach 1:
The invention extracts the navigation function from external markers (bar codes on the floor) and embeds it within the robot itself through onboard sensors and processors. The robot carries its own reference frame and can determine its position by sensing the environment and comparing it to its internal map, eliminating the need for external bar code targets and their associated operational constraints
Data Source
AI summary
Provided is a method for determining a coverage path of a robotic device, including: capturing, with a sensor, spatial data of the environment; detecting, with a processor, at least one obstacle within the environment based on the spatial data; determining, with the processor, a first working zone within the environment; determining, with the processor, a coverage path within the first working zone that accounts for at least one of the obstacles detected within the first working zone; actuating, with the processor, a robotic device to drive along the coverage path within the first working zone; and wherein the processor determines an adapted coverage path when a new obstacle is detected and wherein the processor actuates the robotic device to drive along the adapted coverage path.