Cleaning robot and driving method thereof
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Solution Overview
Problem
Current cleaning robots face inefficiencies in navigation, battery life, and productivity due to frequent stops for obstacles, imprecise navigation systems, and the need for specialized technicians to update maps, making them less effective and practical for large environments.
Innovation Solution
A cleaning robot with a motorized vehicle unit, position sensors, and a processing unit that uses pre-processed maps to optimize cleaning paths and tasks based on environmental conditions, including obstacle density and dynamics, to minimize cleaning time and maximize quality, with the ability to update paths in real-time and extend battery life.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If the robot operates autonomously in environments with moving obstacles, then the robot can perform cleaning tasks without human intervention, but the frequent stops to avoid obstacles considerably reduce battery life
Solution Approach 1:
The system pre-acquires maps of the work environment and pre-calculates optimized cleaning paths before the robot starts operation. This preliminary preparation allows the robot to follow predetermined efficient routes without frequent stops, as the paths are designed to minimize encounters with moving obstacles based on historical data and environmental analysis.
Solution Approach 2:
The navigation system dynamically adjusts the robot's path in real-time based on detected moving obstacles while maintaining overall route efficiency. The robot can deviate from the planned path when necessary and automatically recalculate to return to the optimized route, balancing autonomous operation with energy conservation.
2Adaptability or versatility
If the robot uses real-time detection to establish work tasks and avoid obstacles, then the robot can adapt to current conditions, but the trajectories are not optimized to maximize productivity
Solution Approach 1:
The system performs preliminary processing to pre-acquire environmental maps and pre-calculate optimized cleaning trajectories before the robot begins operation. These pre-computed paths are designed to maximize productivity by covering the entire area efficiently. During operation, the robot follows these predetermined optimized routes while making minor real-time adjustments for safety.
3Measurement precision
If the robot uses navigation systems with current detection sensors, then the robot can detect its position, but the imprecision in large environments makes it difficult to correct drifts
Solution Approach 1:
The system introduces pre-acquired environmental maps as an intermediary reference framework. These maps provide a detailed geometric representation of the work environment that serves as a reference for correcting position drift. The robot compares its sensor-based position estimates against the map data to detect and correct drift, maintaining accurate navigation even in large environments where sensor precision alone is insufficient.
4Extent of automation
If maps are acquired by the robot system itself, then the robot can operate autonomously, but the process requires high detection times and specialized technicians
Solution Approach 1:
The system performs map acquisition and processing as a preliminary action before the robot begins cleaning operations. The maps are pre-acquired using various methods (laser scanning, camera-based SLAM, or import from existing CAD files) and stored for subsequent use. This eliminates the need for time-consuming real-time map creation during operation and removes the requirement for specialized technicians, as the process is automated and completed in advance.
Data Source
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AI summary
Cleaning robot, comprising: a motorized vehicle unit for moving the robot in a work environment; at least one cleaning implement intended to operate on a surface to be treated; at least one driving unit of said robot for moving it according to a certain path within a work environment; said driving unit comprising: at least one position sensor of said vehicle in said environment; at least one representation map of said environment, stored in a memory; a processing unit which, depending on the signals of the position sensor, defines the position of said robot on said map, and which traces the path travelled by said robot and calculates the path that said robot still has to travel in said environment or at least a part of said path; said processing unit generating steering controls of said vehicle unit corresponding to the actual position detected by the sensors and to the path or to said part of path still to be travelled, which are calculated by the processing unit; at least one energy accumulator provided on board said robot, i.e. in particular a battery,