Robot Handover Grip Stiffness Detection for Reliable Release
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Solution Overview
Problem
Human-robot interactions are inefficient due to a lack of informed sense of touch in robotic systems, leading to awkward and ill-informed handovers compared to the intuitive nature of human-to-human interactions.
Innovation Solution
The system measures grip stiffness of a human receiver using active interrogation through small movements of an object, employing sensors to compute grip stiffness and determine the appropriate time to release the object based on computed grip stiffness thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If robot systems rely on external sensing or primitive signal processing methods for handovers, then device complexity is reduced, but measurement precision and reliability of grip detection deteriorate
Solution Approach 1:
The patent replaces complex external sensing systems with a simplified mechanical approach. The robot hand itself becomes the sensing mechanism by actively moving the object and measuring force responses through basic force sensors, eliminating the need for sophisticated external tactile sensors while achieving accurate grip stiffness measurement through computational methods
Solution Approach 2:
The patent transforms the measurement approach by changing from direct tactile sensing to indirect measurement through active movement. By varying the movement parameters (amplitude, frequency, direction) and computing grip stiffness from force responses, the system achieves high measurement precision using simple sensors combined with computational analysis
2Device complexity
If robot systems use primitive signal processing methods for handovers, then device complexity is reduced, but the reliability and efficiency of human-robot interactions deteriorate
Solution Approach 1:
The patent replaces complex signal processing algorithms with a straightforward mechanical probing method. The robot hand performs active movements and uses basic force sensors to detect grip characteristics, achieving reliable handover through simple mechanical interaction and computational stiffness evaluation rather than sophisticated signal processing
Solution Approach 2:
The robot hand serves dual purposes: it both manipulates the object and senses grip characteristics. The same actuators that move the object also provide the active probing motion, and the force sensors integrated in the hand structure enable self-measurement of grip stiffness without requiring separate complex sensing systems
3Device complexity
If robots lack informed sense of touch, then device complexity is reduced, but the quality and intuitiveness of physical interactions deteriorate
Solution Approach 1:
The patent replaces complex tactile sensing systems with a simplified mechanical probing approach. The robot hand actively moves the object in controlled patterns and uses force sensors to infer grip characteristics, achieving intuitive physical interaction through computational analysis of mechanical responses rather than sophisticated tactile sensing
Solution Approach 2:
The patent introduces active movement as an intermediary between the robot and the object during handover. By inserting a probing motion phase where the robot hand moves the object to elicit grip responses, the system enables intuitive interaction through computational interpretation of force feedback rather than direct complex tactile sensing
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 safe and efficient handoffs by accurately determining when to release an object, minimizing accidental drops and improving the reliability of human-robot interactions.
Implementation Method 1
a force sensor configured to gather force data when the force sensor is moved and the human body contacts the force sensor
Implementation Method 2
The gesture classifying unit is configured to calculate one or more features from the force data and classify the force data based at least partially on the one or more features in order to determine the presence and type of a tactile gesture
Implementation Method 3
computing the grip stiffness of the receiver based on the measured response
Data Source
AI summary
Systems and methods for facilitating handoffs between a robot and a counterpart in accordance with embodiments of the invention are illustrated. One embodiment includes a method for controlling a robot to handoff an object. The method includes steps for presenting an object to a receiver, moving an object to interrogate a grip stiffness of the receiver, and measuring a response to the moving using a set of one or more sensors. The method further includes steps for computing the grip stiffness of the receiver based on the measured response and determining whether to release the object based on the computed grip stiffness.