Robot Area-to-Area Navigation Using Semantic Maps and Backtracking
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing telepresence systems face challenges in ease of use for non-expert users, particularly in unfamiliar environments, requiring continuous manual navigation and being tightly coupled with hardware, which hinders software development and enhancement.
Innovation Solution
A system and method for robot navigation using a camera, odometer, and user interface to generate a semantic map, identify landmarks, and plan paths from a first area to a second area, incorporating speech-based interaction and modular AI components for autonomous navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual navigation capability is provided in existing telepresence systems, then the robot can move within the environment based on remote operator commands, but the operation becomes cumbersome for non-expert users in non-familiar environments requiring continuous user intervention
Solution Approach 1:
The system enables the robot to navigate autonomously by generating its own semantic map of the environment, identifying landmarks, and planning paths without continuous manual intervention. The robot serves itself by performing navigation tasks that would otherwise require operator input, thereby simplifying operation for non-expert users while managing complexity through automated cognitive processing.
2Adaptability or versatility
If existing telepresence systems are tightly coupled with robot hardware, then the system can leverage hardware resources, but software development and enhancement become difficult particularly by third-party developers
Solution Approach 1:
The system segments the telepresence architecture into independent modules: a hardware abstraction layer that interfaces with physical sensors and actuators, a semantic mapping module that processes environmental data, a path planning module that computes navigation routes, and a communication layer that handles user interaction. This modular segmentation enables software developers to work on specific components without affecting the entire system, thereby improving adaptability while managing complexity through clear interface definitions.
Data Source
AI summary
A system and method for navigation of a robot from a first area to a second area in a facility is provided. The present disclosure is providing robot navigation using the ‘Areagoal’ Navigation technique. ‘Areagoal’ class of problem is divided into two subtasks: identifying the area; and navigation from one area to another. The robot starts in first location and goes out of the current area if it is not in the target area. If there are multiple openings from the first area, it needs to select the most statistically close one to the target area and go there. If the target area is not reached, it backtracks to an earlier viable branch position to continue the target area search. The system takes input from RGB-D camera and odometer, while the output is action space (left, right, forward) with goal of moving to target area.