Autonomous Robot Positioning With Adaptive Sensor Selection
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Solution Overview
Problem
Existing self-position estimation technologies for autonomous mobile robots face challenges in achieving high accuracy while reducing calculation load and increasing speed, particularly in environments with few target points and high speeds.
Innovation Solution
An autonomous mobile device equipped with a sensor unit comprising an IMU, wheel speed sensor, and mouse sensor, along with a self-position estimation unit that selectively uses parameters from these sensors based on predetermined conditions to estimate position, leveraging UWB and GNSS for high-speed corrections and line detection for accurate orientation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sensor parameters are used for self-position estimation, then measurement precision is improved, but calculation load increases and processing speed decreases
Solution Approach 1:
The patent dynamically selects sensor parameters based on the robot's current movement state. When the robot moves at high speed, the wheel speed sensor is prioritized for its reliability at high velocities. When moving at low speed, the mouse sensor is used for its precision at low velocities. This dynamic adaptation resolves the contradiction by optimizing the sensor combination according to operating conditions, achieving both high accuracy and efficient processing.
Solution Approach 2:
The patent changes the weighting parameters of different sensors based on movement speed thresholds. The determination unit adjusts which sensor parameters are actively used for position estimation depending on whether the robot is in high-speed or low-speed mode. This parameter adjustment allows the system to maintain high measurement precision while reducing calculation load by activating only the most suitable sensors for current conditions.
2Measurement precision
If multiple sensor parameters are used for self-position estimation, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The determination unit dynamically configures which sensors are active based on movement state, reducing the effective complexity of the sensor system at any given moment. Although multiple sensors are physically present, only the appropriate subset is processed based on current speed conditions, simplifying the operational complexity while maintaining the capability for high-precision estimation when needed.
Solution Approach 2:
The patent extracts and uses only the necessary sensor parameters for the current operating condition. Instead of continuously processing all sensor data, the system extracts only the relevant parameters (wheel speed sensor at high speed, mouse sensor at low speed), reducing computational complexity while preserving measurement precision through selective data utilization.
3Device complexity
If traditional self-position estimation methods are used in wide spaces with few target points, then system simplicity is maintained, but measurement precision deteriorates at high speeds
Solution Approach 1:
The patent creates a universal self-position estimation system that functions accurately across different movement conditions and environments. By integrating multiple sensor types (wheel speed sensor, mouse sensor, IMU) with a determination unit that adapts to various speeds, the system maintains simplicity in wide spaces without target points while achieving high precision at both high and low speeds, making the solution universally applicable.
Data Source
AI summary
The present disclosure relates to an autonomous mobile device, a control method, and a program which enable higher-speed self-position estimation with higher accuracy and with a smaller calculation load. Provided is an autonomous mobile device including: a sensor unit including at least a first sensor that detects an angular velocity, a second sensor that is installed in a housing and detects a speed of a wheel, and a third sensor that detects a displacement amount on a two-dimensional plane; and a self-position estimation unit that estimates a self-position on the basis of parameters calculated by the sensor unit, the self-position estimation unit using a predetermined parameter suitable for a predetermined condition among the parameters of the respective sensors calculated by the sensor unit when estimating the self-position. The present disclosure can be applied to, for example, an autonomous mobile robot device.