Indoor UAV Positioning With LiDAR-IMU Mapping and UWB Coordination
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current technologies face challenges in accurately recognizing the position of unmanned mobile vehicles indoors and enabling effective communication between them due to the limitations of GPS and Wi-Fi signals in indoor environments, restricting the operation of swarm and formation flights in unknown indoor settings.
Innovation Solution
The use of 3D LiDAR for position recognition and ultra-wideband (UWB) communication allows unmanned mobile vehicles to generate local maps of their surroundings, identify unsearched areas, and integrate local maps to create an overall global map, facilitating efficient indoor searches and communication among vehicles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS technology is used for position recognition, then outdoor position accuracy is improved, but indoor position recognition becomes impossible due to signal blockage by building materials
Solution Approach 1:
The patent introduces LiDAR and inertial sensors as intermediary technologies to bridge the gap between outdoor GPS-based positioning and indoor positioning requirements. LiDAR scans the environment to generate point cloud data for position recognition, while inertial sensors provide continuous motion tracking, serving as mediators that enable position recognition in GPS-denied indoor environments.
Solution Approach 2:
The patent replaces the electromagnetic wave-based GPS system with a mechanical/optical-based LiDAR scanning system and inertial measurement system. This substitution allows the unmanned mobile vehicle to achieve position recognition through active light emission and mechanical motion sensing rather than passive reception of satellite signals, thereby enabling operation in indoor environments.
2Length of stationary object
If Wi-Fi communication is used for long-distance communication between unmanned mobile vehicles, then communication range is improved, but communication reliability deteriorates in indoor environments due to signal absorption and reflection by building materials
Solution Approach 1:
The patent changes the communication parameter from Wi-Fi (2.4GHz or 5GHz frequency range) to UWB (3.1-10.6GHz frequency range with very short pulse duration). This parameter change allows the communication system to penetrate building materials more effectively and maintain reliable communication in indoor environments, as UWB signals are less susceptible to absorption and reflection by walls and other structures.
3Measurement precision
If marker-based position recognition systems are installed in indoor environments, then position recognition capability is improved, but system complexity and installation requirements increase
Solution Approach 1:
The patent enables the unmanned mobile vehicle to perform self-positioning using onboard LiDAR and inertial sensors without requiring external marker installation or infrastructure setup. The vehicle autonomously scans the environment, generates point cloud data, and calculates its position based on feature extraction and matching, thereby eliminating the need for complex pre-installed marker systems.
Solution Approach 2:
The patent transitions from two-dimensional marker-based position recognition to three-dimensional point cloud-based position recognition. By utilizing the full 3D spatial information captured by LiDAR, the system can recognize positions and identify obstacles in three-dimensional space, providing more robust and versatile positioning capability without requiring markers on surfaces.
4Productivity
If multiple unmanned mobile vehicles operate simultaneously in unknown indoor environments, then search coverage and efficiency are improved, but coordination and communication between vehicles become more difficult without pre-installed infrastructure
Solution Approach 1:
The patent merges the local maps generated by multiple unmanned mobile vehicles into a unified global map through UWB-based communication and position sharing. Each vehicle independently explores and maps its local environment using LiDAR, then the system integrates these local maps considering the relative positions of vehicles (determined through UWB time-of-flight measurements) to construct a comprehensive global map of the entire indoor space.
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
This solution enables unmanned mobile vehicles to operate effectively in unknown indoor environments by accurately recognizing obstacles, searching uncharted areas, and maintaining communication over wide ranges, thereby enhancing indoor search efficiency and flexibility.
Implementation Method 1
obtaining first motion information using a LiDAR sensor provided on the unmanned mobile vehicle
Implementation Method 2
ultra-wideband (UWB) communication allows unmanned mobile vehicles to generate local maps of their surroundings
Data Source
AI summary
Provided is a method of operating an unmanned mobile vehicle for detecting an indoor environment. The method according to an embodiment of the present disclosure includes obtaining first motion information using a LiDAR sensor provided on the unmanned mobile vehicle, obtaining second motion information using an inertial sensor provided on the unmanned mobile vehicle, performing correction on the first motion information and the second motion information on the basis of error models corresponding to the LiDAR sensor and the inertial sensor, and determining final position information of the unmanned mobile vehicle on the basis of the correction.