Robot Indoor Positioning via Wall Line Map Matching
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Solution Overview
Problem
Conventional methods for locating a moving robot, such as inertial navigation and SLAM, suffer from increased errors over distance and require expensive equipment like GPS, cameras, and scan sensors, making precise indoor positioning challenging and costly.
Innovation Solution
An apparatus and method using a low-cost distance sensor and interior map information to compensate for inertial navigation errors, employing a state quantity detection unit, control unit, and Kalman filter to estimate the robot's position by matching straight line information with a prestored map, without the need for expensive equipment or complex algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If inertial navigation method using encoder sensor and gyro sensor is used, then position detection precision is improved, but error accumulates over distance and cannot be easily compensated
Solution Approach 1:
The patent implements feedback by using distance sensors to continuously measure the robot's position relative to walls and furniture, then comparing these measurements with map data to correct accumulated inertial navigation errors. The system feeds back position correction information to the navigation algorithm, maintaining long-term positioning accuracy without drift.
Solution Approach 2:
The patent introduces map information as an intermediary element that mediates between inertial navigation and absolute positioning. The map serves as a reference framework that allows the system to convert relative position measurements from distance sensors into absolute position corrections, enabling error compensation without requiring direct GPS-like satellite signals.
2Measurement precision
If GPS sensor is used to compensate inertial error, then position accuracy is improved, but GPS is unavailable indoors or in cities with multiple paths
Solution Approach 1:
The patent creates an indoor positioning system that copies GPS functionality using available indoor resources. Instead of relying on satellite signals, the system builds a digital map of the indoor environment and uses distance sensors to query position against this map, effectively copying the absolute positioning capability that GPS provides outdoors.
Solution Approach 2:
The patent replaces the GPS satellite-based electromagnetic system with an indoor mechanical/optical sensing system. Instead of receiving signals from satellites, the robot uses distance sensors to physically measure its environment and compare with stored map data, substituting the external satellite infrastructure with local environmental sensing.
3Measurement precision
If SLAM method is used for position detection and map building, then positioning capability is improved, but expensive camera and scan sensor are required
Solution Approach 1:
The patent replaces expensive, complex sensors with inexpensive distance sensors that have sufficient accuracy for the application. Instead of using costly cameras and scan sensors required by traditional SLAM, the system uses affordable ultrasonic or infrared distance sensors to achieve comparable positioning results through map-matching algorithms.
Solution Approach 2:
The patent makes the distance sensor perform multiple functions: obstacle avoidance, position detection, and map building. Instead of requiring separate specialized sensors for each function, the same inexpensive distance sensor suite used for basic navigation also enables sophisticated positioning through integration with map data, reducing overall system cost and complexity.
Data Source
AI summary
An apparatus and a method of locating a moving robot are disclosed. The apparatus includes a storage unit storing information on straight lines of wall on a map, a state quantity detection unit detecting quantity of state of the robot running along the wall, and a control unit estimating an interior position of the robot by obtaining straight line information based on the detected state quantity and matching the obtained straight line information with the stored straight line information.