Method for developing navigation plan in a robotic floor-cleaning device
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Solution Overview
Problem
Existing robotic floor-cleaning devices often generate less efficient navigation paths compared to those selected by humans, particularly in avoiding obstacles like cords and fragile furniture, highlighting a need for a method to replicate human-like path planning.
Innovation Solution
A robotic device equipped with a processor that receives and saves user-input navigation commands, allowing it to re-execute a saved path plan after a predetermined time, enabling efficient and adaptive navigation by incorporating user-defined preferences and environmental mapping.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If automatic path planning algorithms are used, then the device can navigate autonomously, but the navigation efficiency and obstacle avoidance capability deteriorate compared to human-selected paths
Solution Approach 1:
The system performs preliminary action by capturing and storing human-operated navigation paths as templates before autonomous operation. These pre-recorded paths serve as reference data that the autonomous system can follow, combining human expertise with automated execution to achieve efficient navigation without real-time human intervention.
2Productivity
If human-selected paths are used, then navigation efficiency improves, but the ease of operation and adaptability deteriorate due to manual path planning requirements
Solution Approach 1:
The system applies copying by recording human navigation paths as digital templates that can be repeatedly executed by the autonomous system. Instead of requiring manual path planning for each operation, the system captures the human expert's path once and copies it for future autonomous executions, maintaining high navigation efficiency while dramatically improving ease of operation.
3Adaptability or versatility
If path templates are recorded during human operation, then the system can replicate human-like navigation, but the device complexity increases due to additional recording and storage functionality
Solution Approach 1:
The system achieves universality by designing the processor to perform multiple functions: it processes real-time navigation data, records path templates, stores path data in memory, and executes stored paths during autonomous operation. This multi-functionality allows the system to replicate human-like navigation without requiring separate dedicated hardware for each function, thereby limiting the increase in device complexity.
Data Source
AI summary
Included is a method of path planning for a robotic device, including: receiving, by a processor of the robotic device, a sequence of one or more commands; executing, via the robotic device, the sequence of one or more commands; saving the sequence of one or more commands in memory of the robotic device after a predetermined amount of time from receiving a most recent one or more commands; and re-executing the saved sequence of one or more commands.