Dual-LiDAR Robot Navigation for Uneven Floor Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing robot devices struggle to accurately detect the state of the bottom surface while moving, leading to difficulties in adjusting driving speed and navigating around obstacles effectively, especially in environments with uneven surfaces.
Innovation Solution
A robot device equipped with two LiDAR sensors configured to detect obstacles in opposite directions, allowing the device to obtain bottom information and identify sub-spaces within a larger space. This information is used to determine driving levels associated with each sub-space, enabling the robot to adjust its movement accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a robot device uses a single LiDAR sensor to detect obstacles, then the device structure is simple, but the detection accuracy of bottom surface state is insufficient
Solution Approach 1:
The patent divides the detection task into multiple segments by using two LiDAR sensors positioned at different locations (front and rear of the robot). Each sensor detects obstacles in its respective direction, and the processor combines this segmented data to comprehensively determine bottom surface state, achieving higher detection accuracy without excessive complexity
Solution Approach 2:
The patent adds a spatial dimension to obstacle detection by placing LiDAR sensors at multiple positions (front and rear directions) rather than relying on a single detection point. This multi-dimensional sensing approach enables the robot to map the bottom surface state across different spatial locations, significantly improving detection accuracy
2Adaptability or versatility
If the robot device does not identify sub-spaces with different driving levels, then the control system is simple, but the robot cannot adjust driving speed according to bottom surface conditions
Solution Approach 1:
The processor performs preliminary analysis of bottom surface state data before actual driving, identifying and marking different sub-spaces with their respective driving levels in advance. This preliminary classification enables the robot to proactively adjust its driving speed and behavior when entering specific zones, rather than reacting to conditions in real-time
Solution Approach 2:
The patent applies different driving level characteristics to different spatial zones (sub-spaces) based on their specific bottom surface conditions. Each sub-space is assigned a localized driving level (e.g., first driving level for safe areas, second driving level for caution areas, third driving level for dangerous areas), allowing the robot to adapt its driving behavior to local conditions rather than using a uniform control approach
3Loss of time
If the robot device detects obstacles only in the immediate path, then the sensing system is simple, but the robot cannot anticipate and avoid obstacles in advance
Solution Approach 1:
The dual LiDAR sensor configuration enables preliminary detection of obstacles in both front and rear directions simultaneously. By continuously monitoring the environment ahead and behind the robot, the system can identify potential obstacles before they become immediate threats, allowing the robot to plan avoidance maneuvers in advance and reduce response time
Solution Approach 2:
The system continuously receives feedback from both LiDAR sensors about obstacle positions and bottom surface conditions. This real-time feedback loop allows the processor to dynamically adjust the robot's driving path and speed, anticipating obstacles based on detected patterns and making proactive avoidance decisions rather than reactive responses
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
The robot device can accurately navigate through spaces with varying bottom surfaces by adjusting its speed and route based on real-time sensing data, thereby preventing accidents and ensuring efficient movement.
Implementation Method 1
a first LiDAR sensor configured to detect obstacles in a first direction, a second LiDAR sensor configured to detect obstacles in a second direction that is opposite to the first direction
Data Source
AI summary
A robot device is disclosed. The robot device includes memory, a first LiDAR sensor and a second LiDAR sensor, and at least one processor configured to obtain bottom information about a bottom of a space where the robot device is located based on first sensing data received from the first LiDAR sensor and second sensing data received from the second LiDAR sensor, identify a plurality of sub spaces included in the space based on the bottom information, obtain driving level information including driving levels associated with each of the plurality of sub spaces, and control a movement of the robot device based on a driving level of a sub space corresponding to a location of the robot device, the sub space being among the plurality of sub spaces, and wherein the driving level is obtained from the driving level information stored in memory.