Robot Vacuum Path Planning Around Uneven Floor Areas
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Solution Overview
Problem
Mobile appliances such as robot vacuum cleaners and robot mops face challenges when navigating uneven surfaces, which can lead to damage, getting stuck, or inefficient cleaning paths.
Innovation Solution
The method involves obtaining environment information using sensors like cameras and inertial sensors, identifying uneven areas, and planning a motion path that minimizes negotiations with these areas, thereby reducing the risk of damage and improving cleaning efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the motion path is planned to be as short as possible and cover the entire region, then cleaning efficiency is improved, but the risk of damage from negotiating uneven areas increases
Solution Approach 1:
The system performs preliminary detection of uneven areas using sensors (cameras, inertial sensors, depth sensors) before planning the motion path. By identifying problematic areas in advance, the path planning algorithm can route around them, preventing potential damage while maintaining cleaning efficiency. This is implemented through environment perception modules that map uneven areas and integrate this information into coverage path planning.
Solution Approach 2:
The patent introduces an intermediary layer between environment perception and motion planning - a specialized path planning algorithm that considers uneven area characteristics. This intermediary processes sensor data, identifies negotiable versus non-negotiable uneven areas, and generates optimized paths that balance cleaning coverage with damage avoidance. The intermediary translates raw sensor data into actionable path planning constraints.
2Reliability
If the motion path avoids uneven areas, then reliability is improved, but the path length increases
Solution Approach 1:
The system applies different path planning strategies to different types of uneven areas based on their local characteristics. Negotiable uneven areas (small height differences, soft surfaces) allow the appliance to pass through with minimal path deviation, while non-negotiable uneven areas (large steps, hard edges) trigger path rerouting. This localized quality assessment optimizes the balance between path length and damage avoidance on a case-by-case basis.
Solution Approach 2:
The path planning algorithm dynamically adjusts path parameters based on uneven area characteristics. It modifies path geometry, heading angles, and speed profiles when approaching uneven areas. The system changes motion parameters in real-time to minimize path length while ensuring safe negotiation of detectable uneven areas, using sensor feedback to continuously optimize the trajectory.
3Manufacturing precision
If sensors detect and process uneven area information, then path planning accuracy is improved, but device complexity increases
Solution Approach 1:
The system segments the environment into distinct regions based on uneven area characteristics, creating a simplified representation for path planning. Instead of processing continuous sensor data, the system divides the cleaning area into navigable zones and non-navigable zones, with transition regions. This segmentation reduces computational complexity while maintaining path planning accuracy by focusing processing on critical decision boundaries.
Solution Approach 2:
The system creates simplified copies or models of the physical environment for path planning purposes. It generates a 2D map representation from 3D sensor data, storing uneven area locations, types, and negotiability characteristics in a compressed format. This environmental copy allows complex path planning algorithms to run efficiently on embedded processors without requiring full-resolution sensor processing throughout operation.
Data Source
AI summary
A method for determining a motion path on a surface in an environment, along which motion path a mobile appliance, in particular a robot, preferably a domestic robot or a robot vacuum cleaner, is intended to move. The method includes obtaining environment information and determining a region of the surface intended to be covered by the motion of the mobile appliance; determining, while taking into account the environment information, whether within the region there is at least one uneven area in the surface that can be negotiated by the mobile appliance; and determining the motion path while taking into account the at least one uneven area, if there is one. A mobile appliance is also described.