Implement Trajectory Estimation Using IMU Motion Constraints
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing machine systems requiring accurate implement positioning, such as in construction or mining, often necessitate the use of accelerometers and gyroscopes on both the vehicle body and implement, increasing cost and complexity.
Innovation Solution
A method utilizing an IMU attached to the implement to determine its motion and estimate its trajectory by constraining movement to specific planes, employing Kalman filters to estimate positions based on sensor data, thereby reducing the need for multiple sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If accelerometers and gyroscopes are mounted on both the vehicle body and implement, then the positioning accuracy is improved, but the device complexity and cost increase
Solution Approach 1:
The patent extracts the positioning function from a complex multi-sensor system and implements it using only an IMU mounted on the implement. By taking out the vehicle body sensors and relying solely on implement-mounted sensors combined with motion constraint models, the system achieves accurate positioning while reducing device complexity and cost.
Solution Approach 2:
The patent introduces motion constraint models (planar motion constraints) as an intermediary between the IMU measurements and the final position estimation. These constraint models act as a mediator that enables accurate positioning with reduced sensors by incorporating physical knowledge about the implement's motion characteristics.
2Measurement precision
If accelerometers and gyroscopes are mounted on both the vehicle body and implement, then the positioning accuracy is improved, but the cost increases
Solution Approach 1:
The patent removes the expensive vehicle body sensors from the system, keeping only the necessary IMU on the implement. This extraction of unnecessary components directly reduces system cost while maintaining positioning accuracy through the use of motion constraint models.
Solution Approach 2:
The patent employs a simpler, more cost-effective sensor configuration (single IMU on implement) compared to the expensive dual-sensor system. By accepting the limitations of a single IMU and compensating through algorithmic constraints, the system achieves a cost-effective solution suitable for manufacturing.
3Device complexity
If motion is constrained to specific planes with selective estimation modes, then the implementation complexity is reduced, but the adaptability to general motion decreases
Solution Approach 1:
The patent implements dynamic estimation modes that can adapt between different motion constraints (first plane, second plane, or unconstrained). The system dynamically selects the appropriate estimation mode based on the actual motion characteristics, providing both simplified computation when constraints apply and full adaptability when they don't.
Solution Approach 2:
The patent changes the parameters of the estimation algorithm based on the detected motion type. When motion is constrained to a plane, the algorithm uses reduced-parameter models; when unconstrained, it uses full-parameter models. This parameter adaptation maintains accuracy across different motion scenarios while optimizing 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 approach allows for accurate implement positioning without the need for additional sensors on the vehicle body, reducing complexity and cost while maintaining precise trajectory estimation.
Implementation Method 1
receiving sensor data from an IMU attached to the implement and indicative of the movement of the implement
Implementation Method 2
employing Kalman filters to estimate positions based on sensor data
Implementation Method 3
in the presence of gravity disturbance in the sensor data
Data Source
AI summary
The present disclosure relates to a method of operating a machine comprising an implement and a machine for performing such a method. The implement is configured for motion in at least three degrees of freedom. In response to an input, movement of the implement from first to second positions is constrained to a first motion in a first plane or a second motion in a second plane. Sensor data received from an IMU attached to the implement is indicative of the movement of the implement. A first or second estimation mode is selected based upon a determination that the movement is the first or second motion. The first or second estimation mode is implemented to estimate the trajectory of the implement and the second position based upon the sensor data.