Los Angeles, CA, United States
Los Angeles, CA, United States

Time filter

Source Type

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.


Grant
Agency: National Science Foundation | Branch: | Program: SBIR | Phase: Phase II | Award Amount: 711.87K | Year: 2015

The broader impact/commercial potential of this project is to provide a new standard of quantifying touch for industries currently relying on qualitative data from expert sensory panels (the tactile equivalent of professional wine tasters). Advancing the understanding of the role and function of tactile sensing in perception and manipulation is also essential if robots are to behave like humans. Studies have demonstrated that humans who cannot feel due to permanent disease or temporary anesthesia perform poorly in fine manipulation tasks (similar to even the best robotic systems without touch). The research proposed in this project is the next step to bring tactile sensing and sensory-motor intelligence to the next generation of robotics. The successful demonstration of a tactile sensor with perceptual similarity to the human fingertip would mark substantial progress in the field of telemanipulation, bringing the world one step closer to remote haptic perception. This Small Business Innovation Research (SBIR) Phase 2 project seeks to develop the world's first standard of human tactile perception. It has been proposed that tactile recognition presents a more difficult problem than vision and hearing, requiring not only intelligent sensory processing, but also intelligent algorithms to select and control movements, which have a tremendous influence on what is sensed. Artificial sensors that mimic the mechanical properties and sensitivity of the human fingertip have not existed until recently. The research proposed herein will test hypotheses that a biologically inspired robotic system can measure properties that correspond to subjective percepts, descriptors and associations that humans use to characterize objects by touch.


Grant
Agency: NSF | Branch: Standard Grant | Program: | Phase: | Award Amount: 175.81K | Year: 2014

This Small Business Innovation Research (SBIR) Phase I project aims to develop a robotic instrument to provide quantitative characterization of surface properties that humans can perceive by touch. In contrast to machine vision, which operates on images
captured passively with video cameras, machine touch requires physical interaction between the robotic sensors and the object. In fact, tactile signals are affected more by the choice of exploratory movement than by the properties of the object, making selection and control of these movements essential. Current generations of robots rely on primitive contact sensors that are of little use in enabling more human-like perception, movement, dexterity and reflexes. Robots equipped with more humanlike tactile perception and intelligent exploratory strategies will be used to characterize and identify common objects with accuracy and speed similar to humans. They will be able to learn and continuously improve their performance as they interact with objects over time.

The broader impact/commercial potential of this project will be the enabling of advanced, autonomous functionality in the next generation of robots. Robots need to be able to perceive the world and interact with the world more like humans in order to better work alongside us in unstructured environments. Assistive robots for care of the disabled and the elderly are but one example of how next generation robotics will improve the quality of life for many. Better understanding of the haptic properties of consumer products will facilitate development of new products that ?feel? better to human users and the development of quality control systems to assure that those products consistently attain those desirable properties during manufacture. Because these robots employ biomimetic strategies for haptic perception, their performance can be compared to that of humans to provide insights into the perceptual and cognitive strategies employed by the human mind.


Grant
Agency: NSF | Branch: Standard Grant | Program: | Phase: SMALL BUSINESS PHASE II | Award Amount: 711.87K | Year: 2015

The broader impact/commercial potential of this project is to provide a new standard of quantifying touch for industries currently relying on qualitative data from expert sensory panels (the tactile equivalent of professional wine tasters). Advancing the understanding of the role and function of tactile sensing in perception and manipulation is also essential if robots are to behave like humans. Studies have demonstrated that humans who cannot feel due to permanent disease or temporary anesthesia perform poorly in fine manipulation tasks (similar to even the best robotic systems without touch). The research proposed in this project is the next step to bring tactile sensing and sensory-motor intelligence to the next generation of robotics. The successful demonstration of a tactile sensor with perceptual similarity to the human fingertip would mark substantial progress in the field of telemanipulation, bringing the world one step closer to remote haptic perception.

This Small Business Innovation Research (SBIR) Phase 2 project seeks to develop the worlds first standard of human tactile perception. It has been proposed that tactile recognition presents a more difficult problem than vision and hearing, requiring not only intelligent sensory processing, but also intelligent algorithms to select and control movements, which have a tremendous influence on what is sensed. Artificial sensors that mimic the mechanical properties and sensitivity of the human fingertip have not existed until recently. The research proposed herein will test hypotheses that a biologically inspired robotic system can measure properties that correspond to subjective percepts, descriptors and associations that humans use to characterize objects by touch.


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.


Grant
Agency: National Science Foundation | Branch: | Program: SBIR | Phase: Phase I | Award Amount: 149.81K | Year: 2014

This Small Business Innovation Research (SBIR) Phase I project aims to develop a robotic instrument to provide quantitative characterization of surface properties that humans can perceive by touch. In contrast to machine vision, which operates on images captured passively with video cameras, "machine touch" requires physical interaction between the robotic sensors and the object. In fact, tactile signals are affected more by the choice of exploratory movement than by the properties of the object, making selection and control of these movements essential. Current generations of robots rely on primitive contact sensors that are of little use in enabling more human-like perception, movement, dexterity and reflexes. Robots equipped with more humanlike tactile perception and intelligent exploratory strategies will be used to characterize and identify common objects with accuracy and speed similar to humans. They will be able to learn and continuously improve their performance as they interact with objects over time. The broader impact/commercial potential of this project will be the enabling of advanced, autonomous functionality in the next generation of robots. Robots need to be able to perceive the world and interact with the world more like humans in order to better work alongside us in unstructured environments. Assistive robots for care of the disabled and the elderly are but one example of how next generation robotics will improve the quality of life for many. Better understanding of the haptic properties of consumer products will facilitate development of new products that ?feel? better to human users and the development of quality control systems to assure that those products consistently attain those desirable properties during manufacture. Because these robots employ biomimetic strategies for haptic perception, their performance can be compared to that of humans to provide insights into the perceptual and cognitive strategies employed by the human mind.


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


Patent
SynTouch LLC | Date: 2016-09-19

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.


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 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.

Loading SynTouch LLC collaborators
Loading SynTouch LLC collaborators