Implement State Estimator for Terrain-Based Machine Sensor Fusion
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Solution Overview
Problem
Terrain-based machines, such as bulldozers and pavers, face challenges in accurately controlling the position and movement of their implements due to noise and bias in existing sensor systems, which affect the precision of rotational and translational movements.
Innovation Solution
The implementation of a system that includes a translational chassis movement indicator, an implement inclinometer with accelerometers and angular rate sensors, and an implement state estimator using a fusion algorithm to generate accurate state estimates, with a weighting factor to balance sensor signals and mitigate noise effects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing sensor systems are used to control implement position and movement, then the system is simpler and easier to manufacture, but measurement precision and reliability deteriorate due to noise and bias
Solution Approach 1:
The patent combines multiple sensor types (accelerometers, angular rate sensors, and translational chassis movement indicators) into a unified sensor fusion system. The implement state estimator integrates signals from all these sensors to generate a comprehensive implement state estimate, thereby achieving high measurement precision through combined sensor data while managing the complexity through systematic signal processing.
Solution Approach 2:
The implement state estimator acts as an intermediary that processes and fuses data from multiple sensors. It applies a fusion algorithm that weights and combines signals from accelerometers, angular rate sensors, and chassis movement indicators to produce an accurate implement state estimate, mediating between raw sensor data and control decisions.
2Reliability
If multiple sensors are combined to reduce noise effects, then measurement precision improves, but device complexity and computational requirements increase
Solution Approach 1:
The system implements feedback through the implement state estimator, which continuously processes sensor signals and generates implement state estimates that feed back into the control system. The weighting factor mechanism provides adaptive feedback by adjusting the contribution of each sensor based on signal quality, thereby improving reliability while managing computational complexity through intelligent signal weighting.
Solution Approach 2:
The patent employs parameter changes by dynamically adjusting the weighting factor in the fusion algorithm. This weighting factor modulates the influence of different sensor signals based on their reliability and noise characteristics, allowing the system to adapt to varying operating conditions and maintain high reliability without requiring overly complex processing for all scenarios.
3Measurement precision
If sensor signals are processed with weighting factors to mitigate noise, then measurement precision improves, but computational complexity increases
Solution Approach 1:
The weighting factor serves as a adjustable parameter that controls the balance between different sensor inputs. By changing this parameter based on signal quality and noise levels, the system achieves accurate state estimates without requiring maximum computational power for all operations, thus balancing precision with computational efficiency.
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
This system enhances the automated control of terrain-based machine implements by improving the accuracy of rotational and translational movements, reducing noise-induced errors and biases, thereby enhancing operational precision and reliability.
Implementation Method 1
an implement accelerometer, which provides a measurement indicative of acceleration of the terrain-based implement in one or more translational or rotational degrees of freedom
Implementation Method 2
an implement angular rate sensor, which provides a measurement of a rate at which the terrain-based implement is rotating in one or more degrees of rotational freedom
Data Source
AI summary
Terrain-based machines are provided comprising a translational chassis movement indicator, a terrain-based implement, an implement inclinometer, and an implement state estimator. The translational chassis movement indicator provides a measurement indicative of movement of the machine chassis in one or more translational degrees of freedom. The implement inclinometer comprises (i) an implement accelerometer, which provides a measurement indicative of acceleration of the terrain-based implement in one or more translational or rotational degrees of freedom and (ii) an implement angular rate sensor, which provides a measurement of a rate at which the terrain-based implement is rotating in one or more degrees of rotational freedom. The implement state estimator generates an implement state estimate that is based at least partially on (i) implement position signals from an implement angular rate sensor and an implement accelerometer, and (ii) signals from the translational chassis movement indicator and the implement inclinometer.