Modeling and Control of Shapeshifting Ferrofluidic Robots

171824-Thumbnail Image.png
Description
Magnetic liquids called ferrofluids have been used in applications ranging from audio speaker cooling and rotary pressure seals to retinal detachment surgery and implantable artificial glaucoma valves. Recently, ferrofluids have been investigated as a material for use in magnetically controllable…

Magnetic liquids called ferrofluids have been used in applications ranging from audio speaker cooling and rotary pressure seals to retinal detachment surgery and implantable artificial glaucoma valves. Recently, ferrofluids have been investigated as a material for use in magnetically controllable liquid droplet robotics. Liquid droplet robotics is an emerging technology that aims to apply control theory to manipulate fluid droplets as robotic agents to perform a wide range of tasks. Furthermore, magnetically controlled micro-robotics is another popular area of study where manipulating a magnetic field allows for the control of magnetized micro-robots. Both of these emerging fields have potential for impact toward medical applications: liquid characteristics such as being able to dissolve various compounds, be injected via a needle, and the potential for the human body to automatically filter and remove a liquid droplet robot, make liquid droplet robots advantageous for medical applications; while the ability to remotely control the torques and forces on an untethered microrobot via modulating the magnetic field and gradient is also highly advantageous. The research described in this dissertation explores applications and methods for the electromagnetic control of ferrofluid droplet robots. First, basic electrical components built from fluidic channels containing ferrofluid are made remotely tunable via the placement of ferrofluid within the channel. Second, a ferrofluid droplet is shown to be fully controllable in position, stretch direction, and stretch length in two dimensions using proportional-integral-derivative (PID) controllers. Third, control of a ferrofluid’s position, stretch direction, and stretch length is extended to three dimensions, and control gains are optimized via a Bayesian optimization process to achieve higher accuracy. Finally, magnetic control of both single and multiple ferrofluid droplets in two dimensions is investigated via a visual model predictive control approach based on machine learning. These achievements take both liquid droplet robotics and magnetic micro-robotics fields several steps closer toward real-world medical applications such as embedded soft electronic health monitors, liquid-droplet-robot-based drug delivery, and automated magnetically actuated surgeries.
Date Created
2022
Agent

Design and Control of a Lizard-inspired Tube Inspector Robot

171766-Thumbnail Image.png
Description
Tubes and pipelines serve as a major component of several units in power plants and oil, gas, and water transmission. These structures undergo extreme conditions, where temperature and pressure vary, leading to corroding of the pipe over time, creating defects…

Tubes and pipelines serve as a major component of several units in power plants and oil, gas, and water transmission. These structures undergo extreme conditions, where temperature and pressure vary, leading to corroding of the pipe over time, creating defects in them. A small crack in these tubes can cause major safety problems, so a regular inspection of these tubes is required. Most power plants prefer to use non-destructive testing procedures, such as long-range ultrasonic testing and phased array ultrasonic testing, to name a few. These procedures can be carried out with the help of crawlers that go inside the pipes. One of the main drawbacks of the current robotic tube inspection robots is the lack of maneuverability over complex tubular structures and the inability to traverse non-ferromagnetic pipelines. The main motivation of this project is to create a robotic system that can grab onto ferromagnetic and non-ferromagnetic tubes and move along those, move onto adjacent tubes, and maneuver around flanges and bends in the tube. Furthermore, most of the robots used for inspection rely on roller balls and suction-based components that can allow the robot to hold on to the curved surface of the tube. These techniques fail when the surface is rough or uneven, which has served as an inspiration to look at friction-based solutions. Lizards are known for their agile locomotion, as well as their ability to grab on any surface irrespective of the surface texture. The work presented here is focused on the design and control of a lizard-inspired tube inspection robot that can be used to inspect complex tubular structures made of any material.
Date Created
2022
Agent

Validating Granular Scaling Laws for Wheel/Screw Geometries

171752-Thumbnail Image.png
Description
Building and optimizing a design for deformable media can be extremely costly. However, granular scaling laws enable the ability to predict system velocity and mobility power consumption by testing at a smaller scale in the same environment. The validity of…

Building and optimizing a design for deformable media can be extremely costly. However, granular scaling laws enable the ability to predict system velocity and mobility power consumption by testing at a smaller scale in the same environment. The validity of the granular scaling laws for arbitrarily shaped wheels and screws were evaluated in materials like silica sand and BP-1, a lunar simulant. Different wheel geometries, such as non-grousered and straight and bihelically grousered wheels were created and tested using 3D printed technologies. Using the granular scaling laws and the empirical data from initial experiments, power and velocity were predicted for a larger scaled version then experimentally validated on a dynamic mobility platform. Working with granular media has high variability in material properties depending on initial environmental conditions, so particular emphasis was placed on consistency in the testing methodology. Through experiments, these scaling laws have been validated with defined use cases and limitations.
Date Created
2022
Agent

Analyzing a Soft, Pneumatically Actuated, Torso Stabilizing Device to Reduce the Risk of Falls Among the Elderly

Description
Over the past decade, fall related injuries and death among individuals 65 and older due to osteosarcopenia have increased significantly. To reduce the risk of recurrent falls among the elderly caused by osteosarcopenia, a soft-body pneumatically stabilizing device is designed.…

Over the past decade, fall related injuries and death among individuals 65 and older due to osteosarcopenia have increased significantly. To reduce the risk of recurrent falls among the elderly caused by osteosarcopenia, a soft-body pneumatically stabilizing device is designed. A few different actuation methods are considered, both rigid and soft body actuators, before deciding the best fit for the design goals of the wearable assistive device. Much of the design is developed through numerically modeling and analyzing the human upper body as an inverted pendulum. Through this method, common characteristics of falling behavior are identified to develop a control system that counteracts falling motion with pneumatically produced forces. An emphasis on human-oriented design provides much of the framework for translating the numerical model of forces into a device that prioritizes user comfort without sacrificing assistive performance.
Date Created
2022-12
Agent

Sagittal Plane Dynamic Modeling and Control of Aerial Manipulator for Phytobiopsy

168636-Thumbnail Image.png
Description
The ability for aerial manipulators to stay aloft while interacting with dynamic environments is critical for successfully in situ data acquisition methods in arboreal environments. One widely used platform utilizes a six degree of freedom manipulator attached to quadcoper or…

The ability for aerial manipulators to stay aloft while interacting with dynamic environments is critical for successfully in situ data acquisition methods in arboreal environments. One widely used platform utilizes a six degree of freedom manipulator attached to quadcoper or octocopter, to sample a tree leaf by maintaining the system in a hover while the arm pulls the leaf for a sample. Other system are comprised of simpler quadcopter with a fixed mechanical device to physically cut the leaf while the system is manually piloted. Neither of these common methods account or compensate for the variation of inherent dynamics occurring in the arboreal-aerial manipulator interaction effects. This research proposes force and velocity feedback methods to control an aerial manipulation platform while allowing waypoint navigation within the work space to take place. Using these methods requires minimal knowledge of the system and the dynamic parameters. This thesis outlines the Robot Operating System (ROS) based Open Autonomous Air Vehicle (OpenUAV) simulations performed on the purposed three degree of freedom redundant aerial manipulation platform.
Date Created
2022
Agent

A Soft Robotic Hip Exosuit (SR-HExo) for Assistance and Rehabilitation of Human Locomotion

168484-Thumbnail Image.png
Description
The Soft Robotic Hip Exosuit (SR-HExo) was designed, fabricated, and tested in treadmill walking experiments with healthy participants to gauge effectivity of the suit in assisting locomotion and in expanding the basin of entrainment as a method of rehabilitation. The…

The Soft Robotic Hip Exosuit (SR-HExo) was designed, fabricated, and tested in treadmill walking experiments with healthy participants to gauge effectivity of the suit in assisting locomotion and in expanding the basin of entrainment as a method of rehabilitation. The SR-HExo consists of modular, compliant materials to move freely with a user’s range of motion and is actuated with X-oriented flat fabric pneumatic artificial muscles (X-ff-PAM) that contract when pressurized and can generate 190N of force at 200kPa in a 0.3 sec window. For use in gait assistance experiments, X-ff-PAM actuators were placed anterior and posterior to the right hip joint. Extension assistance and flexion assistance was provided in 10-45% and 50-90% of the gait cycle, respectively. Device effectivity was determined through range of motion (ROM) preservation and hip flexor and extensor muscular activity reduction. While the active suit reduced average hip ROM by 4o from the target 30o, all monitored muscles experienced significant reductions in electrical activity. The gluteus maximus and biceps femoris experienced electrical activity reduction of 13.1% and 6.6% respectively and the iliacus and rectus femoris experienced 10.7% and 27.7% respectively. To test suit rehabilitative potential, the actuators were programmed to apply periodic torque perturbations to induce locomotor entrainment. An X-ff-PAM was contracted at the subject’s preferred gait frequency and, in randomly ordered increments of 3%, increased up to 15% beyond. Perturbations located anterior and posterior to the hip were tested separately to assess impact of location on entrainment characteristics. All 11 healthy participants achieved entrainment in all 12 experimental conditions in both suit orientations. Phase-locking consistently occurred around toe-off phase of the gait cycle (GC). Extension perturbations synchronized earlier in the gait cycle (before 60% GC where peak hip extension occurs) than flexion perturbations (just after 60% GC at the transition from full hip extension to hip flexion), across group averaged results. The study demonstrated the suit can significantly extend the basin of entrainment and improve transient response compared to previously reported results and confirms that a single stable attractor exists during gait entrainment to unidirectional hip perturbations.
Date Created
2021
Agent

Characterization of Human Postural Balance under Compliance and Deep Learning for Predicting Environmental Conditions during Postural Balance

168324-Thumbnail Image.png
Description
This thesis work presents two separate studies:The first study assesses standing balance under various 2-dimensional (2D) compliant environments simulated using a dual-axis robotic platform and vision conditions. Directional virtual time-to-contact (VTC) measures were introduced to better characterize postural balance from…

This thesis work presents two separate studies:The first study assesses standing balance under various 2-dimensional (2D) compliant environments simulated using a dual-axis robotic platform and vision conditions. Directional virtual time-to-contact (VTC) measures were introduced to better characterize postural balance from both temporal and spatial aspects, and enable prediction of fall-relevant directions. Twenty healthy young adults were recruited to perform quiet standing tasks on the platform. Conventional stability measures, namely center-of-pressure (COP) path length and COP area, were also adopted for further comparisons with the proposed VTC. The results indicated that postural balance was adversely impacted, evidenced by significant decreases in VTC and increases in COP path length/area measures, as the ground compliance increased and/or in the absence of vision (ps < 0.001). Interaction effects between environment and vision were observed in VTC and COP path length measures (ps ≤ 0.05), but not COP area (p = 0.103). The estimated likelihood of falls in anterior-posterior (AP) and medio-lateral (ML) directions converged to nearly 50% (almost independent of the foot setting) as the experimental condition became significantly challenging. The second study introduces a deep learning approach using convolutional neural network (CNN) for predicting environments based on instant observations of sway during balance tasks. COP data were collected from fourteen subjects while standing on the 2D compliant environments. Different window sizes for data segmentation were examined to identify its minimal length for reliable prediction. Commonly-used machine learning models were also tested to compare their effectiveness with that of the presented CNN model. The CNN achieved above 94.5% in the overall prediction accuracy even with 2.5-second length data, which cannot be achieved by traditional machine learning models (ps < 0.05). Increasing data length beyond 2.5 seconds slightly improved the accuracy of CNN but substantially increased training time (60% longer). Importantly, averaged normalized confusion matrices revealed that CNN is much more capable of differentiating the mid-level environmental condition. These two studies provide new perspectives in human postural balance, which cannot be interpreted by conventional stability analyses. Outcomes of these studies contribute to the advancement of human interactive robots/devices for fall prevention and rehabilitation.
Date Created
2021
Agent

Modeling Mobility in Cohesive Granular Media

164931-Thumbnail Image.png
Description

Exploration of icy moons in the search for extra-terrestrial life is becoming a major focus in the NASA community. As such, the Exobiology Extant Life Surveyor (EELS) robot has been proposed to survey Saturn's Moon, Enceladus. EELS is a snake-like…

Exploration of icy moons in the search for extra-terrestrial life is becoming a major focus in the NASA community. As such, the Exobiology Extant Life Surveyor (EELS) robot has been proposed to survey Saturn's Moon, Enceladus. EELS is a snake-like robot that will use helically grousered wheels to propel itself forward through the complex terrains of Enceladus. This moon's surface is composed of a mixture of snow and ice. Mobility research in these types of terrains is still under-explored, but must be done for the EELS robot to function. As such, this thesis will focus on the methodologies required to effectively simulate wheel interaction with cohesive media from a computational perspective. Three simulation tools will be briefly discussed: COMSOL Multiphysics, EDEM-ADAMS, and projectChrono. Next, the contact models used in projectChrono will be discussed and the methodology used to implement a custom Johnson Kendall Roberts (JKR) collision model will be explained. Finally, initial results from a cone penetrometer test in projectChrono will be shown. Qualitatively, the final simulations look correct, and further work is being done to quantitatively validate them as well as simulate more complex screw geometries.

Date Created
2022-05
Agent

Perturbation-based Training on Compliant Surfaces to Improve Balance in Children with Cerebral Palsy

164786-Thumbnail Image.png
Description

Children with cerebral palsy suffer from balance deficits that may greatly reduce their quality of life. However, recent advancements in robotics allow for balance rehabilitation paradigms that provide greater control of the training environment and more robust measurement techniques. Previous…

Children with cerebral palsy suffer from balance deficits that may greatly reduce their quality of life. However, recent advancements in robotics allow for balance rehabilitation paradigms that provide greater control of the training environment and more robust measurement techniques. Previous works have shown functional balance improvement using standing surface perturbations and compliant surface balancing. Visual feedback during balance training has also been shown to improve postural balance control. However, the combined effect of these interventions has not been evaluated. This paper presents a robot-aided rehabilitation study for two children with cerebral palsy on a side-specific performance-adaptive compliant surface with perturbations. Visual feedback of the participant’s center of pressure and weight distribution were used to evaluate successful balance and trigger perturbations after a period of successful balancing. The platform compliance increased relative to the amount of successful balance during each training interval. Participants trained for 6 weeks including 10, less than 2 hours long, training sessions. Improvements in functional balance as assessed by the Pediatric Balance Scale, the Timed 10 Meter Walk Test, and the 5 Times Sit-to-Stand Test were observed for both participants. There was a reduction in fall risk as evidenced by increased Virtual Time to Contact and an increase in dynamic postural balance supported by a faster Time to Perturb, Time to Stabilize, and Percent Stabilized. A mixed improvement in static postural balance was also observed. This paper highlights the efficacy of robot-aided rehabilitation interventions as a method of balance therapy for children with cerebral palsy.

Date Created
2021-12
Agent

Magnetic Needle Steering and Applications for Less Invasive
Surgery Methodology

164508-Thumbnail Image.png
Description

Medical technology, while improving greatly with time, often requires a sacrifice in the form of invasiveness in order to reach target areas within the body, such as the brain, liver, or heart. This project aims to utilize a magnetic, flexible…

Medical technology, while improving greatly with time, often requires a sacrifice in the form of invasiveness in order to reach target areas within the body, such as the brain, liver, or heart. This project aims to utilize a magnetic, flexible needle design to reach these target areas for surgery and drug administration with minimal invasiveness. The metallic needle tip is guided by an external system consisting of a UR16e robotic arm with a magnetic end effector. As a longer running project, the primary focuses of this research are to develop the system by which the robotic arm guides the needle, investigate and implement fiber Bragg grating sensors as a means of real time path imaging and feedback, and conduct preliminary tests to validate that the needle is accurately controlled by the robotic arm. Testing with different mediums such as gel or phantom tissue, and eventually animal experiments will follow in a future publication due to time constraints.

Date Created
2022-05
Agent
Subscribe to Marvi, Hamidreza