Machine Learning Object Orientation via Impulse Surface Actuation
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Solution Overview
Problem
Existing robotic systems lack flexibility in orienting objects in any desired pose, requiring reconfiguration for each part and being time-consuming and labor-intensive, especially with varying shapes and sizes, limiting their applicability in mass customization scenarios.
Innovation Solution
A robotic assembly using machine learning-based control with a set of actuators and a closed-loop controller that applies impulse forces to orient objects in a desired pose without significant takt time increase, utilizing a learned function to map object states to control commands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If hard automation and single-part orientation systems are used, then manufacturing precision for specific parts is improved, but adaptability to different parts and mass customization is worsened
Solution Approach 1:
The patent implements a universal part orientation system that can handle multiple different parts and orientations using a single reconfigurable platform. The system uses a database of part models and generated impulse commands that can be applied to various part types, eliminating the need for dedicated hard automation for each part while maintaining precise orientation control.
Solution Approach 2:
The system changes operational parameters dynamically based on the specific part being processed. By storing part-specific models and generating customized impulse commands for each part type, the system adapts its control parameters to achieve precise orientation for diverse parts without physical reconfiguration.
2Manufacturing precision
If custom programs are created for each desired orientation, then orientation precision is improved, but device complexity and programming time are worsened
Solution Approach 1:
The patent creates a digital model (copy) of each part in a database that captures its geometric and physical properties. Instead of writing custom control programs for each orientation, the system uses these part models to automatically generate appropriate impulse commands, significantly reducing programming complexity while maintaining orientation accuracy.
Solution Approach 2:
The system performs self-programming by automatically generating control commands based on the part model and desired orientation. The impulse command generator creates the necessary control sequences without requiring manual programming for each part-orientation combination, reducing device complexity and setup time.
3Adaptability or versatility
If reconfiguration of hard automation is performed for each part, then adaptability is improved, but productivity and time consumption are worsened
Solution Approach 1:
The patent replaces physical reconfiguration of hard automation with a software-based control system. Instead of mechanically reconfiguring the orientation system for each part, the system uses a database of part models and generates appropriate control commands, eliminating time-consuming physical reconfiguration while maintaining full adaptability.
Solution Approach 2:
The system performs preliminary actions by pre-storing part models and pre-generating impulse commands in a database. When a new part needs to be oriented, the system retrieves the pre-prepared model and commands, eliminating the need for time-consuming reconfiguration and enabling immediate processing.
4Adaptability or versatility
If multiple actuators are used to cover all possible orientations, then adaptability is improved, but device complexity and cost are worsened
Solution Approach 1:
The patent applies partial action by using a limited set of impulse actuators that apply forces at specific locations and angles. Instead of providing continuous multi-axis actuation, the system uses discrete impulse actions that are sufficient to achieve the desired orientation changes, reducing actuator complexity while maintaining full orientation coverage through intelligent command generation.
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
Enables efficient and flexible object orientation in any desired pose, reducing human intervention and handling times, and seamlessly integrating into existing systems without reconfiguration.
Implementation Method 1
the actuator is configured to apply an impulse to the object with a force governed by a control command
Data Source
Figure 1A
Figure 1B
Figure 2A
AI summary
A robotic controller controls orientation of an object in a desired orientation. The controller obtains pose data indicative of a location and an orientation of the object on a supporting surface and determines one or more control commands for actuating actuators, corresponding to the location and orientation of the object on the supporting surface. The actuators are activated according to the one or more control commands to apply impulse forces to the supporting surface with a likelihood of changing the orientation of the object to the desired orientation. The controller iteratively repeats these procedures until the object is oriented in the desired orientation.