Road Structure Recognition for Map-Free Movement Guidance
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Solution Overview
Problem
Conventional technologies for visually impaired individuals, such as guide dogs and robots, face challenges in providing movement guidance without pre-constructed maps, leading to difficulties in navigating new areas and high maintenance costs.
Innovation Solution
A device and method that utilizes LiDAR or RGBD sensors to recognize road structure and direction, converting 3-D depth sensing data into depth images to determine movement directions based on user input, enabling navigation without relying on precise maps.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a robot uses pre-constructed maps for navigation, then navigation reliability is improved, but adaptability to new areas deteriorates
Solution Approach 1:
The system performs preliminary construction of road structure information databases by collecting and storing road structure data (sidewalks, roads, crosswalks, obstacles) in advance using sensors and mapping algorithms. This pre-processed information enables the robot to navigate new areas without requiring real-time map construction, resolving the contradiction between reliability and adaptability.
2Adaptability or versatility
If a robot operates in areas without pre-constructed maps, then adaptability to new areas is improved, but navigation reliability deteriorates
Solution Approach 1:
The robot autonomously constructs road structure information by using its own sensors (LiDAR, cameras, depth sensors) to detect and map the environment in real-time. The system independently processes sensor data to identify road structures, determine positions, and generate navigation paths without external map inputs, enabling reliable operation in new areas.
3Ease of operation
If conventional guide robots are used, then movement guidance function is improved, but ease of operation deteriorates due to maintenance requirements
Solution Approach 1:
The system replaces complex mechanical navigation systems with sensor-based perception and software-based road structure recognition. By using LiDAR, depth cameras, and image processing algorithms to identify road structures and generate navigation paths, the system eliminates the need for pre-constructed physical maps and reduces mechanical complexity, making the robot easier to operate and maintain.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables visually impaired individuals to navigate safely and freely by recognizing road structures and directions, providing guidance similar to trained guide dogs, and can be used with portable devices or conventional robots without map changes.
Implementation Method 1
A device and method that utilizes LiDAR or RGBD sensors to recognize road structure and direction
Data Source
AI summary
There is provided a method of providing movement guidance based on road structure recognition. The method includes setting a movement mode corresponding to orientation indication that is input by a user, converting, into a depth image, three-dimensional (3-D) depth sensing data that have been input, recognizing information on the structure and direction of a road in the depth image, and determining a movement direction corresponding to the movement mode based on the recognized information on the structure and direction of the road.