Autonomous Navigation Mapping With Multi-Device Obstacle Sensing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for navigation and self-localization of autonomously moving processing devices rely heavily on local data processing and storage, which can be resource-intensive and limit the accuracy of environment maps, especially when detecting obstacles from different perspectives.
Innovation Solution
A method where an accessory device records environmental data and transmits it to an external server for processing, allowing the generation of an environment map that can be combined with data from the processing device, enabling more accurate obstacle detection and navigation by utilizing diverse perspectives and reducing the need for local data processing resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If environmental data is processed locally on the processing device, then real-time navigation control is achieved, but device resources and computational burden increase
Solution Approach 1:
The patent extracts the environmental data processing function from the processing device and relocates it to an external server. The accessory device collects environmental data and transmits it to the external server for map generation and processing, while the processing device only receives navigation commands. This extraction reduces the computational burden and resource consumption of the processing device while maintaining reliable navigation control through centralized processing.
2Measurement precision
If environment maps are generated using single-perspective data, then processing simplicity is maintained, but obstacle detection accuracy decreases
Solution Approach 1:
The patent merges environmental data from multiple sources including the accessory device and the processing device itself into a comprehensive environment map on the external server. By combining data from different perspectives and locations, the system achieves more accurate obstacle detection and comprehensive environmental understanding, while the complexity is managed through centralized server processing rather than distributed device processing.
Data Source
AI summary
A method for the navigation and self-location of an autonomously moving processing device uses an environment map within an environment, wherein environment data of the environment are collected and processed to form an environment map. To support the navigation and self-location of the processing device advantageously, an additional autonomously moving device collects environmental data of the environment for the processing device, and environmental data are transmitted to the processing device. A system consists of an autonomously moving processing device and an additional autonomously moving device.