Virtual World Navigation Engine for Low-SLAM Robot Routing
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Solution Overview
Problem
Current autonomous mobile robots face challenges in navigating complex environments with obstacles and structures like stairs, often requiring significant human intervention and heavy processing for path determination using sensors and SLAM, which can be cumbersome and inefficient.
Innovation Solution
A system and method utilizing a virtual world system with navigational virtual objects and a navigation engine that computes and updates navigation routes based on three-dimensional geolocation coordinates, allowing autonomous robots to navigate through a virtual replica connected to motion mechanisms, reducing reliance on real-time sensor data and SLAM maps.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If sensors and SLAM are used to locate obstacles and generate real-time maps for navigation, then navigation capability in complex environments is improved, but processing load and computational complexity increase significantly
Solution Approach 1:
The system pre-generates a virtual replica of the environment and pre-computes multiple possible navigation paths before the robot needs to navigate. This preliminary preparation reduces the real-time processing load during actual navigation, as the robot can select from pre-computed paths rather than generating them on-the-fly using heavy SLAM algorithms.
Solution Approach 2:
The patent creates a virtual copy (virtual replica) of the real environment with virtual objects corresponding to real objects. This virtual model serves as a simplified representation that can be processed more efficiently than raw sensor data, allowing the navigation engine to compute routes in the virtual space and transfer them to the physical robot, reducing the computational burden on the robot's onboard processors.
2Reliability
If human operators are involved to ensure smoother displacement of robots, then navigation safety is improved, but operational efficiency and autonomy decrease
Solution Approach 1:
The navigation system is designed to be self-sufficient by automatically generating virtual replicas, computing navigation paths, and executing them without continuous human intervention. The system uses onboard sensors to update the virtual model and autonomously recalculates paths when obstacles are detected, enabling the robot to navigate independently while maintaining safety through automated monitoring and path adjustment.
3Measurement precision
If real-time sensor data and SLAM maps are processed for path determination, then navigation accuracy is improved, but computing time and energy consumption increase
Solution Approach 1:
The system performs preliminary processing by creating the virtual replica and computing multiple navigation paths in advance, before real-time navigation is needed. This shifts the computational workload from real-time operation to offline preparation, significantly reducing the computing time required during actual navigation while maintaining accuracy through the use of pre-computed optimal paths.
Solution Approach 2:
The patent extracts the computationally intensive SLAM and path planning functions from the robot's onboard processor and relocates them to a separate navigation server or cloud-based system. The robot only needs to send its current state and receive navigation commands, extracting the heavy processing burden from the mobile device and reducing its computing time and energy consumption.
Data Source
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AI summary
A system, method, autonomous mobile robot, and computer readable media enabling location-based autonomous navigation using a virtual world system. The system comprises at least one server computer of a server computer system comprising at least one processor and memory storing a virtual world system comprising at least one virtual object being spatially defined by virtual three-dimensional geolocation coordinates matching the three-dimensional geolocation coordinates of a corresponding real world object; and a navigation engine configured to compute the navigation route of at least one autonomous mobile robot based on the navigation destination data and considering the three-dimensional geolocation coordinates of the at least one virtual object. The navigation engine enables the at least one autonomous mobile robot to autonomously navigate the real world through a virtual replica of the at least one autonomous mobile robot comprised in the virtual world system connected to one or more corresponding motion mechanisms and circuitry.