Robot Slope Localization Correction via IMU Pose Compensation
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Solution Overview
Problem
Existing localization methods for wheeled mobile robots, particularly in indoor environments, fail to accurately compensate for localization errors caused by slopes and bumps, leading to inaccuracies in obstacle avoidance, planning, and decision-making.
Innovation Solution
A slope localization correction method using inertial measurement elements to measure triaxial acceleration and angular velocity, calculating robot pose through Euler angle matrices, and compensating for localization errors by determining the presence of slopes based on pitch and roll angles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the combination of vision and wheeled mileage encoder is used for localization, then the localization method is widely used in robotics, but the localization error caused by slope and severe bumps cannot be solved
Solution Approach 1:
An inertial measurement unit (IMU) is introduced as an intermediary component to detect slope information and generate compensation data. The IMU acts as a mediator between the physical slope environment and the localization algorithm, providing acceleration and orientation data that help correct localization errors caused by slopes and bumps without requiring changes to the existing vision or encoder systems.
Solution Approach 2:
The system changes the parameter representation by incorporating acceleration data and orientation angles from the IMU into the localization calculation. By adding these new parameters (acceleration along movement direction, orientation angle) to the traditional position and velocity parameters, the system can account for slope effects and improve localization accuracy in challenging terrains.
2Measurement precision
If slope element is set when map is built for compensation, then localization can be compensated at slope position, but the inflexible compensation manner causes inaccurate localization when robot rotates and moves in multiple directions
Solution Approach 1:
The compensation approach transitions from static (pre-defined slope elements in map) to dynamic (real-time IMU-based compensation). The system continuously updates compensation values based on current acceleration and orientation data from the IMU, allowing the robot to handle slopes dynamically while moving in any direction, rather than relying on pre-mapped static compensation zones.
Solution Approach 2:
The robot performs self-compensation by using its own IMU sensors to detect slope conditions and calculate correction values. Instead of relying on externally prepared map data, the system uses the robot's inherent sensing capabilities to autonomously adapt to slope environments, making the compensation flexible and direction-agnostic.
3Measurement precision
If virtual wall is set at slope to prevent robot from going over, then localization errors caused by slope are avoided, but the operating boundaries of the robot are limited
Solution Approach 1:
Instead of avoiding slopes (which would require virtual walls and limit operating area), the system converts the harmful slope-induced localization errors into beneficial learning opportunities. The IMU detects slope conditions and transforms this previously problematic information into useful compensation data, allowing the robot to operate on slopes while maintaining accurate localization.
Solution Approach 2:
The approach inverts the traditional solution by not preventing the robot from entering slope areas, but rather enabling accurate operation within those areas. Instead of using virtual walls to exclude slopes from the operating area, the system actively compensates for slope effects, turning the previously restricted zones into viable operating territories.
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
Provides real-time, robust, and precise correction of localization errors due to slopes and bumps, ensuring accurate robot positioning and operation without the need for artificial slope measurement or virtual walls, enhancing environmental adaptability and reducing localization jumps.
Implementation Method 1
measuring a triaxial acceleration and a triaxial angular velocity of the robot by the inertial measurement element
Implementation Method 2
calculating the pose of the robot through a first Euler angle anti-rotation matrix formed by the triaxial acceleration and a second Euler angle anti-rotation matrix formed by the triaxial angular velocity
Data Source
Figure 1~2
Figure 3~4
AI summary
A slope location correction method, comprising the following steps: measuring location data, in a predetermined area, of a robot by using an inertial measurement element of the robot, and calculating a pose of the robot in the predetermined area according to the location data; determining whether there is a slope in the predetermined area by means of the pose of the robot; and if it is determined that there is a slope in the predetermined area, compensating for a location error at the slope by using the pose corresponding to the slope. The present application further relates to a slope location correction apparatus, a robot and a readable storage medium.