Multi-Sensor Robotic Mower Mapping Without Boundary Wires
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Robotic mowers currently require boundary wires for operation, which are time-consuming to set up and limit the accuracy of positioning, making it difficult to ensure they only service specific areas of a yard without manual intervention.
Innovation Solution
A robotic vehicle equipped with an onboard positioning module, detection module, and mapping module, utilizing sensors like GPS, cameras, and 2.5D sensors to generate accurate maps and maintain boundaries without physical wires, allowing autonomous operation within defined areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If boundary wires are used to define operating areas, then the robotic mower can operate autonomously within defined boundaries, but the setup becomes time-consuming and complex
Solution Approach 1:
The patent removes the boundary wire component entirely from the system. Instead of using physical wires to define boundaries, the robotic mower uses natural boundaries (fences, walls, hedges) already present in the environment, combined with sensor detection and map generation capabilities to operate autonomously without artificial boundary markers.
Solution Approach 2:
The patent introduces a mapping module and sensor system as intermediaries between the robotic mower and the environment. These components create a digital representation of the area, allowing the mower to understand and navigate boundaries without physical wires. The map serves as a mediator that translates environmental features into navigational information.
2Reliability
If boundary wires are installed to define service areas, then the robotic mower can stay within designated zones, but the installation process is difficult and time-consuming
Solution Approach 1:
The patent eliminates the boundary wire installation process entirely. The system uses pre-existing environmental boundaries (fences, walls, hedges) detected by sensors to define service areas, removing the time-consuming task of installing and configuring physical boundary wires while maintaining reliable area confinement.
Solution Approach 2:
The mapping module performs preliminary mapping of the environment during an initial survey phase, creating a digital map that identifies boundaries and service areas before the mower begins operation. This preliminary action eliminates the need for time-consuming boundary wire installation during setup.
3Extent of automation
If positioning equipment is used to determine vehicle location, then the robotic mower can navigate autonomously, but the accuracy is insufficient for precise area definition
Solution Approach 1:
The patent combines multiple sensing modalities (cameras, LIDAR, ultrasonic sensors, infrared sensors) to create a comprehensive detection system. This fusion of different sensor types compensates for the limitations of individual positioning systems, achieving high-precision location determination and boundary detection through multi-sensor integration.
Solution Approach 2:
The mapping module acts as an intermediary that processes sensor data to create a detailed digital representation of the environment. This map provides precise spatial information and boundary definitions that enhance the accuracy of positioning beyond what raw sensor data alone could achieve, enabling precise area definition and navigation.
4Measurement precision
If multiple sensors are integrated for accurate mapping, then the robotic vehicle can generate reliable maps and detect features accurately, but the device complexity increases
Solution Approach 1:
The patent designs the sensor network and mapping module to serve multiple functions simultaneously: boundary detection, obstacle detection, area mapping, navigation, and feature identification. This multi-functionality reduces the need for separate specialized systems, managing complexity while maintaining high mapping accuracy through versatile sensor utilization.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
A method for recording data from at least one sensor of a robotic vehicle responsive to the robotic vehicle transiting a portion of a parcel and determining a confidence score associated with the recorded data for each of a plurality of potential detection events. The confidence score may correspond to a probability that the recorded data corresponds to an object or feature. The method may further include generating map data comprising one or more objects or features correlated to potential detection events based at least in part on the confidence score of the respective objects or features.