A hierarchical sensorimotor control framework for human-in-the-loop robotic hands.

Human manual dexterity relies critically on touch. Robotic and prosthetic hands are much less dexterous and make little use of the many tactile sensors available. We propose a framework modeled on the hierarchical sensorimotor controllers of the nervous system to link sensing to action in human-in-the-loop, haptically enabled, artificial hands

Research regarding development and application of tactile sensing for robots

制度:新 ; 報告番号:甲3063号 ; 学位の種類:博士(工学) ; 授与年月日:2010/2/25 ; 早大学位記番号:新532

A demonstration and comparative analysis of haptic performance using a Gough-Stewart platform as a wearable haptic feedback device

In many hazardous work environments, contact tasks ranging from manufacturing to disassembly to emergency response are performed by industrial manipulators. Due to the hazardous and complex nature of these environments, teleoperation is often employed. When such is the case, the operator is left to interpret a large amount of data during task completion due to the complexity of modern robotic systems and the possible complexity of the tasks. This information is usually processed visually but can lead to sensory overload. To mitigate this, the information processing can also be distributed through other modes of sensory such as auditory or haptic. The University of Texas at Austin's TeMoto hands-free interface reduces the burden on the operator of commanding remote systems by enabling the use of gestural and verbal commands to complete a range of tasks, but the removal of a mechanical interactive device from the operator interface complicates the inclusion of haptic feedback. In this work, a standalone Gough-Stewart platform previously configured as a wearable haptic feedback device for the Nuclear and Applied Robotics Group at the University of Texas at Austin provides real-time haptic feedback to the unconstrained hand(s) of the operator. In doing so, this haptic interface can be employed with the intent of enhancing situational awareness and minimizing operator stress by imparting forces and torques to the user based on those imparted on the end-effector of the industrial manipulator. While multiple technical issues and human factor issues must be addressed, this effort focuses on integrating the system and evaluating its performance for various industrial manipulator designs and sensor modalities. After testing various digital signal processing techniques, functionality was demonstrated among one series-elastic and two rigid industrial manipulators, each with different force/torque data acquisition characteristics and a comparative analysis in haptic performance was performed. Furthermore, it was demonstrated with the TeMoto hands-free teleoperation system. Overall, the demonstrations and experiments performed in this work prove the system to be a viable, hardware agnostic means of haptic feedback and a strong basis for future effortsMechanical Engineerin

Neuromorphic hardware for somatosensory neuroprostheses

In individuals with sensory-motor impairments, missing limb functions can be restored using neuroprosthetic devices that directly interface with the nervous system. However, restoring the natural tactile experience through electrical neural stimulation requires complex encoding strategies. Indeed, they are presently limited in effectively conveying or restoring tactile sensations by bandwidth constraints. Neuromorphic technology, which mimics the natural behavior of neurons and synapses, holds promise for replicating the encoding of natural touch, potentially informing neurostimulation design. In this perspective, we propose that incorporating neuromorphic technologies into neuroprostheses could be an effective approach for developing more natural human-machine interfaces, potentially leading to advancements in device performance, acceptability, and embeddability. We also highlight ongoing challenges and the required actions to facilitate the future integration of these advanced technologies

Robotic Manipulation of Environmentally Constrained Objects Using Underactuated Hands

Robotics for agriculture represents the ultimate application of one of our society\u27s latest and most advanced innovations to its most ancient and vital industry. Over the course of history, mechanization and automation have increased crop output several orders of magnitude, enabling a geometric growth in population and an increase in quality of life across the globe. As a challenging step, manipulating objects in harvesting automation is still under investigation in literature. Harvesting or the process of gathering ripe crops can be described as breaking environmentally constrained objects into two or more pieces at the desired locations. In this thesis, the problem of purposefully failing (breaking) or yielding objects by a robotic gripper is investigated. A failure task is first formulated using mechanical failure theories. Next, a grasp quality measure is presented to characterize a suitable grasp configuration and systematically control the failure behavior of the object. This approach combines the failure task and the capability of the gripper for wrench insertion. The friction between the object and the gripper is used to formulate the capability of the gripper for wrench insertion. A new method inspired by the human pre-manipulation process is introduced to utilize the gripper itself as the measurement tool and obtain a friction model. The developed friction model is capable of capturing the anisotropic behavior of materials which is the case for most fruits and vegetables.The limited operating space for harvesting process, the vulnerability of agricultural products and clusters of crops demand strict conditions for the manipulation process. This thesis presents a new sensorized underactuated self-adaptive finger to address the stringent conditions in the agricultural environment. This design incorporates link-driven underactuated mechanism with an embedded load cell for contact force measurement and a trimmer potentiometer for acquiring joint variables. The integration of these sensors results in tactile-like sensations in the finger without compromising the size and complexity of the proposed design. To obtain an optimum finger design, the placement of the load cell is analyzed using Finite Element Method (FEM). The design of the finger features a particular round shape of the distal phalanx and specific size ratio between the phalanxes to enable both precision and power grasps. A quantitative evaluation of the grasp efficiency by constructing a grasp wrench space is also provided. The effectiveness of the proposed designs and theories are verified through real-time experiments. For conducting the experiments in real-time, a software/hardware platform capable of dataset management is crucial. In this thesis, a new comprehensive software interface for integration of industrial robots with peripheral tools and sensors is designed and developed. This software provides a real-time low-level access to the manipulator controller. Furthermore, Data Acquisition boards are integrated into the software which enables Rapid Prototyping methods. Additionally, Hardware-in-the-loop techniques can be implemented by adding the complexity of the plant under control to the test platform. The software is a collection of features developed and distributed under GPL V3.0

NASA space station automation: AI-based technology review

Research and Development projects in automation for the Space Station are discussed. Artificial Intelligence (AI) based automation technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics. AI technology will also be developed for the servicing of satellites at the Space Station, system monitoring and diagnosis, space manufacturing, and the assembly of large space structures