Robot Path Identification Using Reliability-Based Map Areas
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Solution Overview
Problem
Robot devices face significant positional errors while navigating, leading to deviations from their intended movement paths due to inaccuracies in estimating their actual position versus their estimated position, necessitating a method to assess and correct these errors in real-time.
Innovation Solution
A robot device equipped with sensors like LiDAR and cameras that acquire and combine detection data to estimate its position, calculate reliability values based on matching probabilities, and adjust its movement path by identifying areas with sufficient reliability values to ensure accurate navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If the robot device estimates its position based on movement path alone, then the navigation process is simple, but the positional accuracy deteriorates due to error accumulation
Solution Approach 1:
The patent implements feedback by continuously comparing the robot's estimated position (from movement path) with its actual position (detected by sensors like LiDAR and cameras). This comparison generates position error information that is fed back to correct the movement path, preventing error accumulation and maintaining positional accuracy throughout navigation.
Solution Approach 2:
The patent replaces pure mechanical/movement-based position estimation with sensor-based detection systems (LiDAR, cameras). These sensors directly measure the robot's position in the environment, substituting the indirect mechanical estimation method and providing accurate real-time position data for path correction.
2Measurement precision
If the robot device uses sensor-based position detection, then the positional accuracy is improved, but the device complexity increases due to additional sensors and processing
Solution Approach 1:
The patent makes the sensor system multi-functional by using the same sensors (LiDAR, cameras) for both navigation/detection and mapping functions. This universal approach allows the system to achieve accurate position detection without adding dedicated separate systems, thereby reducing overall device complexity while maintaining high positional accuracy.
Solution Approach 2:
The patent merges the position detection function with the existing mapping and navigation systems. By integrating sensor data processing into the unified navigation framework, the system achieves accurate positioning without creating separate complex subsystems, thereby reducing overall system complexity.
3Measurement precision
If the robot device continuously updates movement path, then the positional accuracy is maintained, but the processing time and computational load increase
Solution Approach 1:
The patent applies partial action by updating the movement path only when necessary - specifically when position errors are detected or when approaching critical locations. This selective updating approach maintains positional accuracy without requiring continuous full-path recalculations, thereby reducing computational load and processing time while still achieving the desired accuracy.
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 effectively reduces positional errors by identifying reliable areas and adjusting the movement path, thereby enhancing the robot's ability to accurately navigate and maintain alignment with its intended path.
Implementation Method 1
The sensor may include a light detection and ranging (LiDAR) sensor, the first detection data may include first point cloud data received from the LiDAR sensor
Data Source
AI summary
Provided is a robot device and a method of controlling same. The robot device includes: at least one memory storing at least one instruction; a sensor configured to detect an environment of the robot device and output detection data; and at least one processor configured to execute the at least one instruction to: acquire a map of a space where the robot device is positioned based on the detection data received from the sensor, and a reliability value of each of a plurality of areas of the map, store the map and the reliability value of each of the plurality of areas in the at least one memory, identify at least one area having a reliability value greater than or equal to a critical value, based on the reliability value of each of the plurality of areas, and identify a movement path of the robot device in the space, based on the at least one area.