Autonomous Gripper Selection for Robotic Arms
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Solution Overview
Problem
Current robotic systems are limited in their ability to handle diverse tasks due to the need for human intervention to switch between different gripper types, which restricts their capability to manage various objects of different shapes, sizes, weights, and environmental conditions, leading to inefficiencies and suboptimal performance.
Innovation Solution
A robotic system that autonomously selects and switches between multiple grippers based on task-specific needs using AI, computer vision, and machine learning, allowing for quick detachment and attachment of grippers from a storage area, such as a 'gripper wall', to adapt to different objects and environments without human intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a single robot with a fixed gripper is used, then the robot structure is simple, but it cannot handle diverse objects of different shapes, sizes, and weights
Solution Approach 1:
The patent implements a universal robot system that can perform multiple functions by dynamically switching between different gripper types stored in a library. The robot controller is designed to select and mount appropriate grippers from a standardized library, enabling a single robot to handle diverse objects of different shapes, sizes, and weights without requiring multiple specialized robots.
2Extent of automation
If multiple robots with different grippers are used, then each robot can be optimized for specific tasks, but human intervention is required to switch grippers and the system becomes less autonomous
Solution Approach 1:
The robot system performs self-service by autonomously selecting and mounting appropriate grippers from a standardized library without human intervention. The robot controller automatically determines which gripper is needed based on the task requirements and executes the mounting operation, eliminating the need for operators to manually switch grippers between robots.
3Adaptability or versatility
If a universal gripper is used, then the gripper structure is simple, but it can only handle a selected number of different object types effectively
Solution Approach 1:
The gripper system is segmented into a standardized library of pre-configured gripper types, each optimized for specific object categories. Instead of using a single complex universal gripper, the system divides the gripper functionality into discrete, interchangeable modules stored in a library, allowing the robot to select and mount only the necessary gripper type for each task.
4Productivity
If human operators manually switch grippers, then the gripper selection can be optimized for each task, but the productivity decreases due to manual intervention and time consumption
Solution Approach 1:
The gripper library is pre-configured with multiple gripper types ready for immediate deployment. The robot controller has pre-programmed knowledge of which grippers are available and their capabilities, allowing it to instantly select and mount the appropriate gripper without time-consuming manual intervention or search processes.
Data Source
AI summary
A robotic system with autonomous gripper selection is disclosed. Sensor data is received from a sensor in a workspace. The sensor data is used to determine an end effector to be used to perform a task with respect to an object in the workspace. The determined end effector is autonomously mounted on a free moving end of a robotic arm comprising the robotic system, and the robotic arm and end effector are used to perform the task with respect to the object.