Mobile Robot Position Tracking With Slippage-Corrected Sensor Fusion
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Solution Overview
Problem
Existing robotic devices face challenges in accurately tracking displacement and rotation, especially due to slippage, which affects their ability to generate accurate maps of their environment and maintain thorough coverage.
Innovation Solution
A robotic device equipped with a processor that captures visual, encoder, optoelectronic, and depth sensor readings to determine displacement, estimate corrected positions, and account for slippage by creating an ensemble of possible positions based on wheel rotation and surface readings, selecting the most feasible position.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If encoder sensor readings are used to track displacement, then the robotic device can maintain continuous position tracking, but slippage causes measurement errors that reduce positioning accuracy
Solution Approach 1:
The patent introduces an intermediary system that reconciles conflicting position data from multiple sources. The processor acts as an intermediary, receiving encoder readings and visual sensor data, then using optimization algorithms to determine the most reliable position estimate when sensors provide conflicting information due to slippage or measurement errors
Solution Approach 2:
The system implements feedback by continuously monitoring position discrepancies between encoder readings and visual sensor measurements. When slippage is detected through optimization algorithms, the system adjusts its position estimates and uses this feedback to improve future tracking accuracy, maintaining reliability despite individual sensor failures
2Measurement precision
If multiple sensor types are integrated to improve positioning accuracy, then measurement precision increases, but device complexity increases
Solution Approach 1:
The processor is designed with multi-functionality, serving both as the control unit for navigation and as the optimization engine for sensor data fusion. This universal component approach reduces overall system complexity by eliminating the need for separate dedicated optimization hardware
Solution Approach 2:
The patent merges multiple sensor systems (encoders, visual sensors, depth sensors) and their processing functions into a unified optimization framework. By combining these elements and processing them through a single optimization algorithm, the system achieves high positioning accuracy while managing complexity through integration rather than separate systems
3Adaptability or versatility
If the robotic device operates on uneven surfaces, then adaptability to different environments improves, but slippage increases causing position tracking errors
Solution Approach 1:
The system dynamically adjusts its position estimation strategy based on surface conditions. The optimization algorithm continuously evaluates sensor data reliability and adapts its calculations in real-time, switching between relying more on encoders or visual sensors depending on the detected surface stability and slippage conditions
Solution Approach 2:
The system uses feedback from visual sensors and depth sensors to detect slippage conditions on uneven surfaces. When slippage is detected, the feedback loop adjusts the optimization algorithm to compensate for the inaccurate encoder readings, maintaining measurement precision across varying surface conditions
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
Enhances the robotic device's ability to accurately map its environment and maintain thorough coverage by correcting for slippage and ensuring precise positioning, even in complex or uneven surfaces.
Implementation Method 1
capturing, with an encoder sensor, readings of wheel rotation indicative of displacement of the robotic device
Implementation Method 2
capturing, with an optoelectronic sensor, readings of a driving surface of the environment of the robotic device; determining, with the processor, displacement of the robotic device in two dimensions based on the optoelectronic sensor readings
Implementation Method 3
capturing, with a visual sensor, visual readings to objects within an environment of the robotic device as the robotic device moves within the environment
Implementation Method 4
capturing, with a depth sensor, distances to obstacles as the robot moves within the environment
Data Source
AI summary
Provided is a tangible, non-transitory, machine readable medium storing instructions that when executed by the processor effectuates operations including: capturing visual readings to objects within an environment; capturing readings of wheel rotation; capturing readings of a driving surface; capturing distances to obstacles; determining displacement of the robotic device in two dimensions based on sensor readings of the driving surface; estimating, with the processor, a corrected position of the robotic device to replace a last known position of the robotic device; determining a most feasible element in an ensemble based on the visual readings; and determining a most feasible position of the robotic device as the corrected position based on the most feasible element in the ensemble and the visual readings.