Robot Grasp Control Using 3D Shape Primitives
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Solution Overview
Problem
Current robot systems face challenges in effectively grasping and manipulating objects in diverse environments due to limitations in sensing and control methods, which hinder precise object recognition and optimal grasping strategies.
Innovation Solution
A robot system equipped with sensors and a controller that captures sensor data to generate a platonic representation of objects using three-dimensional shapes, allowing for the selection of appropriate grasp primitives and locations based on object geometry, enabling precise control of end effectors for effective grasping.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If robot systems use traditional sensing and control methods, then the system structure remains simple, but the ability to accurately recognize objects and determine optimal grasping strategies is limited
Solution Approach 1:
The patent segments the complex sensing and control system into distinct functional modules: sensor data acquisition module, platonic representation generation module, grasp primitive selection module, and end effector control module. This modular segmentation allows each module to specialize in specific tasks, improving overall measurement precision while managing system complexity through organized functional decomposition
Solution Approach 2:
The patent introduces platonic representations as an intermediary layer between raw sensor data and grasping control decisions. This intermediary abstraction enables the system to process complex object geometries through simplified geometric models, significantly improving object recognition accuracy without requiring proportionally complex control algorithms
2Adaptability or versatility
If robot systems use simplified grasping methods, then the control system remains simple, but the adaptability to diverse object shapes and environments is reduced
Solution Approach 1:
The patent implements a universal grasping control framework that can handle diverse object shapes and environments through a single integrated system. The framework uses platonic representations to universally model different object geometries and a library of grasp primitives that can be selectively applied based on object characteristics, enabling one system to perform multiple grasping tasks across varied environments
Solution Approach 2:
The patent employs parameter changes by adjusting grasp primitive selection and application parameters based on the specific characteristics of each object detected through sensor data. The system modifies grasping parameters such as contact points, force distribution, and end effector configuration to adapt to diverse object shapes, achieving high grasping versatility through dynamic parameter optimization
3Productivity
If robot systems implement precise object recognition and optimal grasping strategies, then grasping efficiency is improved, but the computational requirements and system complexity increase
Solution Approach 1:
The patent applies preliminary action by pre-processing sensor data into platonic representations before grasping decisions are made. This preliminary transformation of raw data into structured geometric models enables faster and more efficient grasping control, improving productivity by reducing the computational burden during the actual grasping execution phase
Data Source
AI summary
Systems, methods, and control modules for controlling robot systems are described. An object is represented by a platonic representation, which is one or more basic geometric shapes which approximate the object. A library of ways to grasp these basic geometric shapes is accessed, and an appropriate way to grasp a shape is selected and used to grasp the object at a location where the basic geometric shape at least approximately corresponds to the grasp.