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Los Angeles, CA, United States

Grant
Agency: Department of Health and Human Services | Branch: | Program: SBIR | Phase: Phase I | Award Amount: 224.19K | Year: 2014

DESCRIPTION (provided by applicant): Myoelectric prosthetic hand users are severely hampered in their ability to grasp and manipulate fragile objects. In these systems, electromyography (EMG) signals recorded from an amputee's residual muscles are processed to produce an electrical voltage proportional to muscle activation to drive the DC motors of a prosthetic hand. With training, users can voluntarily open, close and stop the hand with proportional control over the speed of the fingertips. If the user applies a continuous EMG signal to grasp an object, the motors driving the fingertips will stall on the object, producing high grasping forces of 30-100N depending on the EMG amplitude. Such high forces make it very challenging to grasp fragile objects without damaging them. Careful control and timing of EMG signals can be used to move the fingers at very slow speeds, stopping them before a fragile object is crushed; however, this approach requires direct vision, intense concentration, and has inconsiste


Grant
Agency: Department of Commerce | Branch: National Institute of Standards and Technology | Program: SBIR | Phase: Phase II | Award Amount: 299.76K | Year: 2014

Robotic actuators exceed human speed, accuracy, and strength, but human hands are regarded as the ultimate in dexterity. We propose this is due absent human-like tactile sensing and intelligent reflexive behaviors in robots. We’ve created multimodal compliant tactile sensors that mimic the sensory ability of the human fingertip and algorithms that fill this absence. In this research we will integrate these with the Schunk Dexterous Hand (SDH). Working with NIST and our partners we will develop measures of robotic grasper dexterity and use them to evaluate our new tactile sensory technology with the older tactile sensors of the SDH. This will lead to a new level of dexterity, enabling advanced applications in industrial automation and assembly.


A compliant tactile sensor may include sponge-like material, a flexible skin, and a fluid pressure sensor. The flexible skin may have a shape, absorb fluid, compress in response to force applied to the sponge-like material, and decompress and return to its original shape when the force is removed. The flexible skin may cover an outer surface of the sponge-like material. The fluid pressure sensor may sense changes in pressure in fluid that is within the sponge-like material caused by a force applied to the flexible skin. A robotic system may include a movable robotic arm, a compliant tactile sensor on the movable robotic arm that senses contact between the compliant tactile sensor and an object during movement of the movable robotic arm and that cushions the effect of that contact, and a reflex system that causes the moveable robotic arm to move in response to commands.


Patent
SynTouch LLC | Date: 2014-01-09

An object investigation and classification system may include an object test system, a data storage system, and a data processing system. The object test system may receive a command to perform at least one action with a test object, perform the at least one action with the test object, and return test information indicative of at least one percept resulting from the at least one action. The data storage system may contain an experience database containing data indicative of multiple classifications and, for each classification, at least one action that was performed with at least one previously-observed reference object having this classification, and at least one percept value that is based in whole or in part on the test information resulting from the at least one action. The data processing system may: a) for each of multiple different classifications, compute or receive an initial prior probability that a test object falls within the classification; b) determine at least one action that should be performed with the test object to obtain at least one percept about the test object that is likely to enable the classification of the test object to be more accurately determined based on the initial prior probabilities and the data within the experience database; c) cause the object test system to perform the at least one action with the test object; d) receive test information from the object test system indicative of at least one percept resulting from the at least one action with the test object; e) compute at least one percept value; f) for each of multiple different classifications, determine a posterior probability that the test object falls within the classification based on the initial prior probability, the at least one percept value, and data within the experience database; g) determine whether any of the posterior probabilities meets or exceeds a threshold; h) if none of the posterior probabilities meet or exceed the threshold, repeat b) through i), substituting the posterior probabilities determined in f) for the initial prior probabilities in b); and/or i) when one or more of the posterior probabilities meets or exceeds the threshold, output information indicative of one or more of the classifications that correspond to the one or more posterior probabilities that meets or exceeds the threshold.


A system may measure, store, and recall at least one tactile property of multiple objects. The system may include one or more biomimetic tactile sensors that have mechanical properties and sensor modalities that are similar to those of human fingertips. The system may perform at least one exploratory movement on one of the objects by moving the biomimetic tactile sensors over a surface of the object. The at least one exploratory movement may be of a type that a human would normally perform on the object to discern the at least one tactile property and may have one or more movement parameters. Each of the movement parameters may fall within a range of movement parameters that would normally be exhibited if a human performed the exploratory movement for the at least one tactile property. The system may determine and store a value of the at least one tactile property based on information provided by the biomimetic tactile sensors in response to the exploratory movement. The determining may use an analytical function that specifies a mathematical relationship between the value and the information provided by the biomimetic tactile sensors that is based on physical phenomena, rather than extracted from data sets by an adaptive algorithm. The system may repeat the same exploratory movement performance, the same determining the value using the same analytical function, and the same storing the determined value for each of the other objects.

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