Robotic Vehicle Parcel Mapping for Minimum-Workload Route Planning
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Solution Overview
Problem
Robotic lawn mowers lack the ability to efficiently map and adapt to varying energy demands across different areas of a parcel of land, leading to inefficient energy usage and potential battery depletion during high workload tasks.
Innovation Solution
Equipping robotic vehicles with sensors to monitor energy output and terrain resistance, allowing for the generation of virtual maps that identify elevated and reduced workload areas, enabling the vehicle to optimize its operational route and battery usage based on these maps.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the robotic vehicle operates in elevated workload areas, then the productivity is improved, but the energy consumption increases and battery depletes faster
Solution Approach 1:
The system performs preliminary mapping of the parcel to identify elevated workload areas before actual operation. This advance knowledge allows the robotic vehicle to plan its route and battery usage strategy beforehand, ensuring it operates in high-energy-demand areas only when sufficiently charged, thus resolving the contradiction between productivity and energy consumption
Solution Approach 2:
The operational schedule is made dynamic and adaptive based on real-time battery state of charge. The system continuously adjusts when and where the robotic vehicle operates by comparing current battery levels against the pre-generated virtual map, allowing flexible optimization of productivity versus energy consumption during operation
2Adaptability or versatility
If the robotic vehicle maps the entire parcel to identify workload areas, then the adaptability is improved, but the time and energy required for mapping increases
Solution Approach 1:
The system performs complete mapping of the parcel once to generate a comprehensive virtual map, but then uses this pre-generated map for subsequent operations without remapping. This approach accepts the initial time investment for complete mapping in exchange for significant time savings in later operations, where the system only needs to query and follow the pre-established workload area information
Solution Approach 2:
The virtual map generation is performed as a preliminary action before actual mowing operations begin. This one-time mapping effort creates a reusable reference that guides all subsequent operations, eliminating the need for repeated mapping and thereby reducing overall time loss while maintaining high adaptability to terrain variations
Data Source
Figure 1
Figure 2A~2B
Figure 3
AI summary
A method for determining and mapping a parcel of land may include receiving positioning-information indicative of position data of a robotic vehicle transiting a parcel at one or more locations on the parcel and receiving workload-information indicative of workload data of a robotic vehicle transiting the parcel at one or more locations on the parcel. The method may further include generating a virtual map of the parcel based on the positioning-information and the workload-information received.