Robot Hand Impedance Control for Stable Grasping
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Solution Overview
Problem
Conventional robot hands fail to naturally and safely grasp objects as they rely solely on finger tips without utilizing the palm, leading to instability when moving or manipulating objects, especially when the object's shape information is incorrect or deviates from the ideal grasp position.
Innovation Solution
A robot hand with a palm and multiple fingers that sets target positions and creates grasp paths using impedance control, allowing the fingers to follow optimal paths, including a quadratic curve based on three target positions, to ensure stable grasping and manipulation of objects, even when the object's shape is not uniform.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional robot hand grasping method is used (only finger tips), then the control is simple, but the grasping stability and naturalness deteriorate
Solution Approach 1:
The patent implements dynamic grasp control by allowing the robot hand to adaptively adjust its grasping posture and force during the grasping process. The control system dynamically modifies finger positions and forces based on real-time feedback, enabling the hand to naturally conform to objects of varying shapes and sizes, thereby improving grasping stability without requiring overly complex predetermined control programs.
Solution Approach 2:
The patent employs feedback mechanisms where the control system continuously monitors the grasping state and adjusts finger positions and forces accordingly. This feedback loop allows the robot hand to detect and correct deviations from optimal grasping postures in real-time, enhancing grasping reliability while maintaining manageable control complexity through iterative refinement rather than complex open-loop control.
2Ease of operation
If impedance control is implemented for natural grasping, then the grasping naturalness improves, but the computational complexity increases
Solution Approach 1:
The patent implements impedance control by dynamically adjusting key parameters including stiffness, damping, and equilibrium position of the robot hand during grasping. These parameter changes enable the hand to exhibit natural, compliant behavior when interacting with objects, adapting to different object properties without requiring overly complex control algorithms. The impedance parameters are modified based on grasp phase and object characteristics, achieving naturalness with manageable computational complexity.
3Adaptability or versatility
If finger tips only are used for grasping, then the device structure is simple, but the manipulation capability deteriorates
Solution Approach 1:
The patent divides the robot hand into multiple functional segments including palm, fingers, and thumb, each capable of independent control and contribution to grasping. This segmentation allows different parts of the hand to perform specialized functions - the palm provides stable base contact, fingers enable precise positioning and wrapping, and thumb adds oppositional capability. This modular segmentation enhances manipulation capability while keeping each component's structure relatively simple and manageable.
Solution Approach 2:
The patent designs the robot hand with multi-functional capability where the same structural components (palm, fingers, thumb) can perform multiple functions depending on the grasping task. The hand can switch between different grasping modes (power grasp, precision grasp, lateral grasp) using the same physical structures, achieving high adaptability and manipulation capability without requiring specialized structures for each function, thus avoiding excessive complexity.
Data Source
AI summary
Disclosed herein is a method of controlling a robot hand similar to a hand of a human being such that the robot hand naturally and safely grasps an object. The robot hand, including fingers and a palm, is capable of naturally and safely grasping an object, by the tip of each finger performing impedance control while following the optimal path on a Cartesian coordinate system, although the robot hand cannot reach a position ideal to grasp the object due to sensor errors or shape information of the object to be grasped is not correctly recognized. Also, the robot hand is capable of stably grasping the object even when moving or manipulating the object.