3D Robot Mapping for Moving Object Identification
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Solution Overview
Problem
Robots operating in dynamic environments like airports, schools, and factories face challenges in creating accurate 3D maps due to varying object heights and temporary structures, leading to inaccuracies in movement and collision avoidance.
Innovation Solution
A robot equipped with multiple sensors (lidar, depth, and ultrasound) calculates and converts height and position information into global coordinates to generate a 3D map, identifying moving objects and updating the map in real-time to ensure accurate navigation and obstacle avoidance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a robot uses multiple sensors to generate a 3-dimensional map reflecting object heights, then the accuracy of robot movement is improved, but the device complexity increases
Solution Approach 1:
The patent combines data from multiple sensors (lidar, depth sensor, ultrasound sensor) to generate a comprehensive 3-dimensional map. The controller integrates information from these different sensing modalities, merging their respective strengths to achieve accurate height and position information while managing system complexity through unified processing.
Solution Approach 2:
The robot system performs multiple functions using the sensor array: it generates 3D maps, identifies moving objects, calculates global coordinates, and navigates autonomously. The same sensor suite serves multiple purposes, from static mapping to dynamic obstacle detection, reducing the need for separate specialized systems.
2Loss of information
If the robot stores information about all objects including moving objects in the 3-dimensional map, then the map completeness is improved, but the movement efficiency of the robot deteriorates
Solution Approach 1:
The system dynamically updates the 3-dimensional map by continuously comparing current sensor data with stored map information. When an object is detected as moving through comparison of successive measurements, the system adapts by excluding it from the static map structure, allowing the map to evolve from a complete but static representation to a dynamic, efficiency-optimized representation.
Solution Approach 2:
The patent extracts and separates moving objects from the static 3-dimensional map. By identifying objects that change position between measurements and removing them from the permanent map storage, the system maintains map completeness for navigation purposes while eliminating distracting moving elements that would reduce movement efficiency.
3Device complexity
If the robot uses a single sensor type for mapping, then the device complexity is reduced, but the measurement precision deteriorates due to varying object heights and temporary structures
Solution Approach 1:
The system changes the sensing parameters by using multiple sensor types with different measurement characteristics. Each sensor type (lidar for distance and angle, depth sensor for depth information, ultrasound for proximity) operates in its optimal parameter range, and their combined data provides comprehensive coverage of objects at varying heights and positions that no single sensor could capture accurately.
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 solution enables the robot to move efficiently without collisions by accurately differentiating between stationary and moving objects, improving map accuracy and reducing errors from individual sensor inaccuracies.
Implementation Method 1
a lidar sensor coupled to the robot to calculate a physical distance between an object and the robot and angle information between the object and the robot
Implementation Method 2
a depth sensor to calculate depth information of an object in one direction from the robot
Implementation Method 3
an ultrasound sensor for sensing a distance of an object within a predetermined radius around the robot
Data Source
AI summary
A method for identifying a moving object in a three-dimensional space and a robot for implementing same is provided. The robot includes a sensing module for calculating height and position information of an object by using two or more sensing units; a movement unit for moving the robot; a map storage unit for storing a three-dimensional map including the height and position information of the object, calculated by the sensing module, in a space in which the robot is moving; and a control unit for controlling the sensing module, the movement unit, and the map storage unit, converting the height and position information of the object calculated by the sensing module into global coordinates, storing, in the three-dimensional map, the height and position information of the object converted into the global coordinates, and removing, from the three-dimensional map, a moving object among objects stored in the map storage unit.