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Robotics Commons

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Full-Text Articles in Robotics

Development Of A Soft Robotic Approach For An Intra-Abdominal Wireless Laparoscopic Camera, Hui Liu Aug 2023

Development Of A Soft Robotic Approach For An Intra-Abdominal Wireless Laparoscopic Camera, Hui Liu

Doctoral Dissertations

In Single-Incision Laparoscopic Surgery (SILS), the Magnetic Anchoring and Guidance System (MAGS) arises as a promising technique to provide larger workspaces and field of vision for the laparoscopes, relief space for other instruments, and require fewer incisions. Inspired by MAGS, many concept designs related to fully insertable magnetically driven laparoscopes are developed and tested on the transabdominal operation. However, ignoring the tissue interaction and insertion procedure, most of the designs adopt rigid structures, which not only damage the patients' tissue with excess stress concentration and sliding motion but also require complicated operation for the insertion. Meanwhile, lacking state tracking of …


Sensor Fusion For Object Detection And Tracking In Autonomous Vehicles, Mohamad Ramin Nabati Aug 2021

Sensor Fusion For Object Detection And Tracking In Autonomous Vehicles, Mohamad Ramin Nabati

Doctoral Dissertations

Autonomous driving vehicles depend on their perception system to understand the environment and identify all static and dynamic obstacles surrounding the vehicle. The perception system in an autonomous vehicle uses the sensory data obtained from different sensor modalities to understand the environment and perform a variety of tasks such as object detection and object tracking. Combining the outputs of different sensors to obtain a more reliable and robust outcome is called sensor fusion. This dissertation studies the problem of sensor fusion for object detection and object tracking in autonomous driving vehicles and explores different approaches for utilizing deep neural networks …


Adaft: A Resource-Efficient Framework For Adaptive Fault-Tolerance In Cyber-Physical Systems, Ye Xu Nov 2017

Adaft: A Resource-Efficient Framework For Adaptive Fault-Tolerance In Cyber-Physical Systems, Ye Xu

Doctoral Dissertations

Cyber-physical systems frequently have to use massive redundancy to meet application requirements for high reliability. While such redundancy is required, it can be activated adaptively, based on the current state of the controlled plant. Most of the time the physical plant is in a state that allows for a lower level of fault-tolerance. Avoiding the continuous deployment of massive fault-tolerance will greatly reduce the workload of CPSs. In this dissertation, we demonstrate a software simulation framework (AdaFT) that can automatically generate the sub-spaces within which our adaptive fault-tolerance can be applied. We also show the theoretical benefits of AdaFT, and …


Learning Multimodal Structures In Computer Vision, Ali Taalimi Aug 2017

Learning Multimodal Structures In Computer Vision, Ali Taalimi

Doctoral Dissertations

A phenomenon or event can be received from various kinds of detectors or under different conditions. Each such acquisition framework is a modality of the phenomenon. Due to the relation between the modalities of multimodal phenomena, a single modality cannot fully describe the event of interest. Since several modalities report on the same event introduces new challenges comparing to the case of exploiting each modality separately.

We are interested in designing new algorithmic tools to apply sensor fusion techniques in the particular signal representation of sparse coding which is a favorite methodology in signal processing, machine learning and statistics to …


Computational Imaging Approach To Recovery Of Target Coordinates Using Orbital Sensor Data, Michael D. Vaughan Aug 2017

Computational Imaging Approach To Recovery Of Target Coordinates Using Orbital Sensor Data, Michael D. Vaughan

Doctoral Dissertations

This dissertation addresses the components necessary for simulation of an image-based recovery of the position of a target using orbital image sensors. Each component is considered in detail, focusing on the effect that design choices and system parameters have on the accuracy of the position estimate. Changes in sensor resolution, varying amounts of blur, differences in image noise level, selection of algorithms used for each component, and lag introduced by excessive processing time all contribute to the accuracy of the result regarding recovery of target coordinates using orbital sensor data.

Using physical targets and sensors in this scenario would be …


Multi-Classifier Fusion Strategy For Activity And Intent Recognition Of Torso Movements, Abhijit Kadrolkar Nov 2016

Multi-Classifier Fusion Strategy For Activity And Intent Recognition Of Torso Movements, Abhijit Kadrolkar

Doctoral Dissertations

As assistive, wearable robotic devices are being developed to physically assist their users, it has become crucial to develop safe, reliable methods to coordinate the device with the intentions and motions of the wearer. This dissertation investigates the recognition of user intent during flexion and extension of the human torso in the sagittal plane to be used for control of an assistive exoskeleton for the human torso. A multi-sensor intent recognition approach is developed that combines information from surface electromyogram (sEMG) signals from the user’s muscles and inertial sensors mounted on the user’s body. Intent recognition is implemented by following …


Neuron Clustering For Mitigating Catastrophic Forgetting In Supervised And Reinforcement Learning, Benjamin Frederick Goodrich Dec 2015

Neuron Clustering For Mitigating Catastrophic Forgetting In Supervised And Reinforcement Learning, Benjamin Frederick Goodrich

Doctoral Dissertations

Neural networks have had many great successes in recent years, particularly with the advent of deep learning and many novel training techniques. One issue that has affected neural networks and prevented them from performing well in more realistic online environments is that of catastrophic forgetting. Catastrophic forgetting affects supervised learning systems when input samples are temporally correlated or are non-stationary. However, most real-world problems are non-stationary in nature, resulting in prolonged periods of time separating inputs drawn from different regions of the input space.

Reinforcement learning represents a worst-case scenario when it comes to precipitating catastrophic forgetting in neural networks. …


A Magnetic Actuated Fully Insertable Robotic Camera System For Single Incision Laparoscopic Surgery, Xiaolong Liu Aug 2015

A Magnetic Actuated Fully Insertable Robotic Camera System For Single Incision Laparoscopic Surgery, Xiaolong Liu

Doctoral Dissertations

Minimally Invasive Surgery (MIS) is a common surgical procedure which makes tiny incisions in the patients anatomy, inserting surgical instruments and using laparoscopic cameras to guide the procedure. Compared with traditional open surgery, MIS allows surgeons to perform complex surgeries with reduced trauma to the muscles and soft tissues, less intraoperative hemorrhaging and postoperative pain, and faster recovery time. Surgeons rely heavily on laparoscopic cameras for hand-eye coordination and control during a procedure. However, the use of a standard laparoscopic camera, achieved by pushing long sticks into a dedicated small opening, involves multiple incisions for the surgical instruments. Recently, single …


Dynamic Simulation And Neuromuscular Control Of Movement: Applications For Predictive Simulations Of Balance Recovery, Misagh Mansouri Boroujeni May 2015

Dynamic Simulation And Neuromuscular Control Of Movement: Applications For Predictive Simulations Of Balance Recovery, Misagh Mansouri Boroujeni

Doctoral Dissertations

Balance is among the most challenging tasks for patients with movement disorders. Study and treatment of these disorders could greatly benefit from combined software tools that offer better insights into neuromuscular biomechanics, and predictive capabilities for optimal surgical and rehabilitation treatment planning. A platform was created to combine musculoskeletal modeling, closed-loop forward dynamic simulation, optimization techniques, and neuromuscular control system design. Spinal (stretch-reflex) and supraspinal (operational space task-based) controllers were developed to test simulation-based hypotheses related to balance recovery and movement control. A corrective procedure (rectus femoris transfer surgery) was targeted for children experiencing stiff-knee gait and how this procedure …


Modeling, Analysis, And Control Of A Mobile Robot For In Vivo Fluoroscopy Of Human Joints During Natural Movements, Matthew A. Young May 2014

Modeling, Analysis, And Control Of A Mobile Robot For In Vivo Fluoroscopy Of Human Joints During Natural Movements, Matthew A. Young

Doctoral Dissertations

In this dissertation, the modeling, analysis and control of a multi-degree of freedom (mdof) robotic fluoroscope was investigated. A prototype robotic fluoroscope exists, and consists of a 3 dof mobile platform with two 2 dof Cartesian manipulators mounted symmetrically on opposite sides of the platform. One Cartesian manipulator positions the x-ray generator and the other Cartesian manipulator positions the x-ray imaging device. The robotic fluoroscope is used to x-ray skeletal joints of interest of human subjects performing natural movement activities. In order to collect the data, the Cartesian manipulators must keep the x-ray generation and imaging devices accurately aligned while …