Robotic Hand Pre-Grasp Control for Multi-Object Transfer
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Solution Overview
Problem
Existing robotic systems struggle to efficiently grasp and transfer multiple objects at once due to challenges in estimating object quantity and pose, occlusion issues, and unpredictable object displacement, leading to inefficiencies in grasping and transferring tasks.
Innovation Solution
A robotic system equipped with a Markov decision process and stochastic grasping techniques, including pre-grasp and end-grasp configurations, to identify optimal hand configurations for grasping multiple objects, leveraging tactile and vision sensors to improve grasping precision and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a robotic system grasps one object at a time, then the grasping control is simple, but the transfer efficiency is low
Solution Approach 1:
The patent segments the grasping control into two distinct phases: pre-grasp configuration (planning finger positions and spread angles before contact) and end-grasp configuration (adjusting after contact based on actual object interaction). This segmentation allows the system to handle multiple objects efficiently by pre-planning configurations for target quantities while maintaining simplicity through standardized phases.
Solution Approach 2:
The system performs preliminary action by identifying pre-grasp configurations before actual object contact occurs. The robotic hand plans finger spread angles and positions in advance based on the target quantity of objects, allowing for more efficient multi-object grasping without requiring complex real-time control during the grasping action itself.
2Adaptability or versatility
If the robotic hand uses fixed grasp configuration, then the control is simple, but the adaptability to different object quantities is poor
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting the spread angle of robotic hand fingers based on the target quantity of objects to be grasped. Different target quantities correspond to different pre-grasp configurations with optimized spread angles, allowing the system to adapt to varying object quantities while maintaining systematic control through parameter optimization.
Data Source
AI summary
Systems and methods for multiple object transferring using robotics. A system includes a robotic hand with a base and fingers capable of grasping objects. A robotic arm is coupled to the robotic hand and is capable of moving the robotic hand. One or more circuits are configured to operate the robotic hand and the robotic arm by identifying a pre-grasp configuration for the robotic hand and executing a transfer routine based on a Markov decision process model to operate the robotic hand and the robotic arm such that they move multiple objects from a first location to a second location.