Autonomous Loading Vehicle Dig Controller
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Solution Overview
Problem
Autonomous excavation of rock piles is challenging due to unpredictable bucket-rock interactions, with existing controllers performing poorly in heterogeneous materials and encountering subsurface irregularities, and requiring complex tuning that is impractical for real-world applications.
Innovation Solution
A dig controller using an adaptive admittance controller and iterative learning controller that adjusts bucket and vehicle motion based on sensor signals from actuators other than the bucket, allowing for dynamic force regulation and learning from previous digs to improve excavation efficiency in varied rock pile conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a discrete dig path controller or compliance controller is used, then the system can operate in homogeneous materials, but it performs poorly when subsurface irregularities are encountered
Solution Approach 1:
The controller transitions from static discrete dig paths to dynamic compliant motion control, allowing the bucket to adapt its motion in real-time based on sensed forces from subsurface irregularities, thereby maintaining reliability across heterogeneous materials
Solution Approach 2:
The system uses force sensors to provide real-time feedback on bucket-rock interactions, enabling the compliance controller to adjust motion dynamically in response to subsurface irregularities, improving adaptability while maintaining excavation performance
2Adaptability or versatility
If a fuzzy logic behaviour-based controller is used, then the system can handle uncertain conditions, but the results are inconsistent and difficult to implement as a commercial product
Solution Approach 1:
The patent replaces complex fuzzy logic behavioral rules with a physics-based compliance controller that uses force feedback and admittance control, achieving consistent results with a more implementable control architecture that relies on fundamental mechanical principles rather than heuristic rules
3Adaptability or versatility
If an admittance-based controller is used to regulate bucket actuator velocity, then the system can adapt to varying rock conditions, but it was never implemented or tested
Solution Approach 1:
The patent performs preliminary tuning of the compliance controller parameters using simulated rock pile data before deployment, ensuring the admittance-based controller is properly calibrated for various rock conditions, thereby enabling both adaptability and proven reliable performance
4Device complexity
If traditional controllers are used, then the system structure is simpler, but complex tuning is required that is impractical for real-world applications
Solution Approach 1:
The compliance controller automatically adapts to different rock conditions through real-time force feedback without requiring manual retuning, making the system self-adjusting and practical for real-world applications where rock pile properties vary
Data Source
Figure 1A
Figure 1B~1D
Figure 2A
AI summary
Provided are dig controller and dig control method embodiments for an autonomous loading vehicle (ALV) used in applications such as mining, construction, and exploration. Embodiments may comprise at least one controller that controls a bucket and/or the ALV in accordance with at least one sensor signal, wherein the at least one sensor signal is representative of interaction between the bucket and the rock pile during a dig. Some embodiments include at least one admittance controller and optionally at least one iterative learning controller (ILC) that uses feedback from at least one previous dig to modify the at least one sensor signal provided to the at least one controller.