Loader Augmented Control for Repetitive Task Learning
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Solution Overview
Problem
Existing power machines, particularly loaders, face challenges in efficiently performing repetitive tasks due to the need for repetitive manual control, which can be tedious and inefficient.
Innovation Solution
Implementing augmented control systems that learn a series of machine operations through a learning mode, set a home position, and autonomously repeat these operations to complete tasks, utilizing controllers and positioning devices for precise alignment and obstacle avoidance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual control is used for repetitive tasks, then the operator can perform tasks with flexibility, but the efficiency and productivity are reduced due to repetitive manual operations
Solution Approach 1:
The loader is equipped with a control system that enables it to perform repetitive tasks autonomously without continuous human intervention. The system learns the task sequence through a learning mode and then executes it automatically, allowing the machine to serve itself in completing routine operations like loading materials onto a trailer.
Solution Approach 2:
The control system performs preliminary learning of the task sequence during a learning mode before actual task execution. By预先 recording the series of operations needed to complete a work task, the system prepares the automated control sequence in advance, enabling efficient repetition without manual intervention during task execution.
2Productivity
If automated control is implemented, then task repetition efficiency is improved, but the device complexity increases due to additional control systems and positioning devices
Solution Approach 1:
The control system is designed to perform multiple functions: it can operate in manual mode for flexible task execution, switch to learning mode to record task sequences, and then execute automated mode to repeat tasks. This multi-functionality allows a single integrated system to handle both simple and complex operational requirements without needing separate specialized systems.
Solution Approach 2:
The patent combines the control system, positioning devices, and learning functionality into an integrated automated control system. By merging these components into a unified system rather than separate systems, the patent reduces overall system complexity while maintaining the capabilities for automated task execution and learning.
3Manufacturing precision
If precise positioning and alignment are achieved, then task accuracy is improved, but the time required for positioning and alignment increases
Solution Approach 1:
The patent replaces manual mechanical positioning and alignment operations with an automated control system that uses positioning devices to determine the loader's location and orientation. This substitution allows for precise positioning through electronic control and calculation rather than manual mechanical adjustment, achieving high accuracy while reducing the time required for positioning tasks.
Data Source
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AI summary
Disclosed embodiments include power machines or loaders (100; 200; 300; 900; 1000; 1200; 1300; 1400), and systems used on loaders, configured to augment the control of the loader to accomplish repetitive tasks. Also disclosed are methods (600, 700, 1100) of learning a task for augmented control of a loader, and methods (5650) of controlling a loader to perform a learned task to provide augmented control of the loader.