Matching Items (30)
Description
In this work, different passive prosthetic ankles are studied. It is observed that complicated designs increase the cost of production, but simple designs have limited functionality. A new design for a passive prosthetic ankle is presented that is simple to manufacture while having superior functionality. This prosthetic ankle design has two springs: one mimicking Achilles tendon and the other mimicking Anterior-Tibialis tendon. The dynamics of the prosthetic ankle is discussed and simulated using Working model 2D. The simulation results are used to optimize the springs stiffness. Two experiments are conducted using the developed ankle to verify the simulation It is found that this novel ankle design is better than Solid Ankle Cushioned Heel (SACH) foot. The experimental data is used to find the tendon and muscle activation forces of the subject wearing the prosthesis using OpenSim. A conclusion is included along with suggested future work.
ContributorsBhat, Sandesh Ganapati (Author) / Redkar, Sangram (Thesis advisor) / Sugar, Thomas (Committee member) / Lee, Hyuglae (Committee member) / Marvi, Hamid (Committee member) / Arizona State University (Publisher)
Created2017
Description
The Basilisk lizard is known for its agile locomotion capabilities on granular and aquatic media making it an impressive model organism for studying multi-terrain locomotion mechanics. The work presented here is aimed at understanding locomotion characteristics of Basilisk lizards through a systematic series of robotic and animal experiments. In this work, a Basilisk lizard inspired legged robot with bipedal and quadrupedal locomotion capabilities is presented. A series of robot experiments are conducted on dry and wet (saturated) granular media to determine the effects of gait parameters and substrate saturation, on robot velocity and energetics. Gait parameters studied here are stride frequency and stride length. Results of robot experiments are compared with previously obtained animal data. It is observed that for a fixed robot stride frequency, velocity and stride length increase with increasing saturation, confirming the locomotion characteristics of the Basilisk lizard. It is further observed that with increasing saturation level, robot cost of transport decreases. An identical series of robot experiments are performed with quadrupedal gait to determine effects of gait parameters on robot performance. Generally, energetics of bipedal running is observed to be higher than quadrupedal operation. Experimental results also reveal how gait parameters can be varied to achieve different desired velocities depending on the substrate saturation level. In addition to robot experiments on granular media, a series of animal experiments are conducted to determine and characterize strategies
exhibited by Basilisk lizards when transitioning from granular to aquatic media.
exhibited by Basilisk lizards when transitioning from granular to aquatic media.
ContributorsJayanetti, Vidu (Author) / Marvi, Hamid (Thesis advisor) / Emady, Heather (Committee member) / Lee, Hyunglae (Committee member) / Arizona State University (Publisher)
Created2018
Description
Robotic swarms can potentially perform complicated tasks such as exploration and mapping at large space and time scales in a parallel and robust fashion. This thesis presents strategies for mapping environmental features of interest – specifically obstacles, collision-free paths, generating a metric map and estimating scalar density fields– in an unknown domain using data obtained by a swarm of resource-constrained robots. First, an approach was developed for mapping a single obstacle using a swarm of point-mass robots with both directed and random motion. The swarm population dynamics are modeled by a set of advection-diffusion-reaction partial differential equations (PDEs) in which a spatially-dependent indicator function marks the presence or absence of the obstacle in the domain. The indicator function is estimated by solving an optimization problem with PDEs as constraints. Second, a methodology for constructing a topological map of an unknown environment was proposed, which indicates collision-free paths for navigation, from data collected by a swarm of finite-sized robots. As an initial step, the number of topological features in the domain was quantified by applying tools from algebraic topology, to a probability function over the explored region that indicates the presence of obstacles. A topological map of the domain is then generated using a graph-based wave propagation algorithm. This approach is further extended, enabling the technique to construct a metric map of an unknown domain with obstacles using uncertain position data collected by a swarm of resource-constrained robots, filtered using intensity measurements of an external signal. Next, a distributed method was developed to construct the occupancy grid map of an unknown environment using a swarm of inexpensive robots or mobile sensors with limited communication. In addition to this, an exploration strategy which combines information theoretic ideas with Levy walks was also proposed. Finally, the problem of reconstructing a two-dimensional scalar field using observations from a subset of a sensor network in which each node communicates its local measurements to its neighboring nodes was addressed. This problem reduces to estimating the initial condition of a large interconnected system with first-order linear dynamics, which can be solved as an optimization problem.
ContributorsRamachandran, Ragesh Kumar (Author) / Berman, Spring M (Thesis advisor) / Mignolet, Marc (Committee member) / Artemiadis, Panagiotis (Committee member) / Marvi, Hamid (Committee member) / Robinson, Michael (Committee member) / Arizona State University (Publisher)
Created2018
Description
The role of robotics mobility is essential in the world of research because it allows humans to perform jobs that are dull, dirty, or dangerous without being physically present. A typical robot environment is one that is smooth and predictable. Screw-powered vehicles (SPV's) have commonly been used in these predictable environment situations such as terrestrial applications like mud and snow. However, a gap remains in SPV's traversing complex environments, particularly debris and granular material. The goal is to study the characteristics of how a SPV might move and generate force in such a granular environment for Earth and space. In our study, the chosen granular environment is soda-lime glass beads for easy characterization. This study with glass beads focuses on two separate approaches. The first approach is using a single screw rotating while the apparatus remains static and analyzing the forces that impact the screw. The second approach includes using a full body craft with two double helix screws and analyzing the translational velocity of the craft. This study presents both experimental and computational results using simulations with Multi-Body Dynamics (MBD) and Discrete Element Method (DEM) software packages to investigate the trends of SPV's in a granular environment.
ContributorsRamirez, Sierra Monique (Author) / Marvi, Hamid (Thesis director) / Emady, Heather (Committee member) / Thoesen, Andrew (Committee member) / Mechanical and Aerospace Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
This thesis presents an approach to design and implementation of an adaptive boundary coverage control strategy for a swarm robotic system. Several fields of study are relevant to this project, including; dynamic modeling, control theory, programming, and robotic design. Tools and techniques from these fields were used to design and implement a model simulation and an experimental testbed. To achieve this goal, a simulation of the boundary coverage control strategy was first developed. This simulated model allowed for concept verification for different robot groups and boundary designs. The simulation consisted of a single, constantly expanding circular boundary with a modeled swarm of robots that autonomously allocate themselves around the boundary. Ultimately, this simulation was implemented in an experimental testbed consisting of mobile robots and a moving boundary wall to exhibit the behaviors of the simulated robots. The conclusions from this experiment are hoped to help make further advancements to swarm robotic technology. The results presented show promise for future progress in adaptive control strategies for robotic swarms.
ContributorsMurphy, Hunter Nicholas (Author) / Berman, Spring (Thesis director) / Marvi, Hamid (Committee member) / Mechanical and Aerospace Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
Chapter 1: Functional Specialization and Arm Length in Octopus bimaculoides<br/>Although studies are limited, there is some evidence that octopuses use their arms for specialized functions. For example, in Octopus maya and O. vulgaris, the anterior arms are utilized more frequently for grasping and exploring (Lee, 1992; Byrne et al., 2006a), while posterior arms are more frequently utilized for crawling in O. vulgaris (Levy et al., 2015). In addition, O. vulgaris uses favored arms when retrieving food and making contact with a T-maze as dictated by their lateralized vision (Byrne, 2006b). O. vulgaris also demonstrates a preference for anterior arms when retrieving food from a Y-maze (Gutnick et. al. 2020). In Octopus bimaculoides bending and elongation were more frequent in anterior arms than posterior arms during reaching and grasping tasks, and right arms displayed deformation more frequently than left arms, with the exception of the hectocotylus (R3) in males (Kennedy et. al. 2020). Given these observed functional differences, the goal of this study was to determine if morphological differences exist between different octopus arm identities, coded as L1-L4 and R1-R4. In particular, the relationship between arm length and arm identity was analyzed statistically. The dataset included 111 intact arms from 22 wild-caught specimens of O. bimaculoides (11 male and 11 female). Simple linear regressions and an analysis of covariance were performed to test the relationship between arm length and a number of factors, including body mass, sex, anterior versus posterior location, and left versus the right side. Mass had a significant linear relationship with arm length and a one-way ANOVA demonstrated that arm identity is significantly correlated with arm length. Moreover, an analysis of covariance demonstrated that independent of mass, arm identity has a significant linear relationship with arm length. Despite an overall appearance of bilateral symmetry, arms of different identities do not have statistically equivalent lengths in O. bimaculoides. Furthermore, differences in arm length do not appear to be related to sex, anterior versus posterior location, or left or right side. These results call into question the existing practice of treating all arms as equivalent by either using a single-arm measurement as representative of all eight or calculating an average length and suggest that morphological analyses of specific arm identities may be more informative.<br/><br/>Chapter 2: Predicting and Analyzing Octopus bimaculoides Sensitivity to Global Anesthetic<br/>Although global anesthetic is widely used in human and veterinary medicine the mechanism and impact of global anesthetic is relatively poorly comprehended, even in well-studied mammalian models. Invertebrate anesthetic is even less understood. In order to evaluate factors that impact anesthetic effectiveness analyses were conducted on 22 wild-caught specimens of Octopus bimaculoides during 72 anesthetic events.Three machine learning models: regression tree, random forest, and generalized additive model were utilized to make predictions of the concentration of anesthetic (percent ethanol by volume) from 11 features and to determine feature importance in making those predictions. The fit of each model was analyzed on three criteria: correlation coefficient, mean squared error, and relative error. Feature importance was determined in a model-specific manner. Predictions from the best performing model, random forest, have a .82 correlation coefficient with experimental values. Feature importance suggests that temperature on arrival and cohabitation factors strongly influence predictions for anesthesia concentration. This likely indicates the transportation process was incurring stress on the animals and that cohabitation was also stressful for the typically solitary O. bimaculoides. This long-term stress could lead to a decline in the animal’s well-being and a lower necessary ethanol concentration (Horvath et al., 2013). This analysis provides information to improve the care of octopus in laboratory settings and furthers the understanding of the effects of global anesthetic in invertebrates, particularly one with a distributed nervous system.
ContributorsSorge, Marieke Alexandria (Author) / Fisher, Rebecca (Thesis director) / Zhao, Yunpeng (Committee member) / Marvi, Hamid (Committee member) / School of Life Sciences (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
Soft continuum robots with the ability to bend, twist, elongate, and shorten, similar to octopus arms, have many potential applications, such as dexterous manipulation and navigation through unstructured, dynamic environments. Novel soft materials such as smart hydrogels, which change volume and other properties in response to stimuli such as temperature, pH, and chemicals, can potentially be used to construct soft robots that achieve self-regulated adaptive reconfiguration through on-demand dynamic control of local properties. However, the design of controllers for soft continuum robots is challenging due to their high-dimensional configuration space and the complexity of modeling soft actuator dynamics. To address these challenges, this dissertation presents two different model-based control approaches for robots with distributed soft actuators and sensors and validates the approaches in simulations and physical experiments. It is demonstrated that by choosing an appropriate dynamical model and designing a decentralized controller based on this model, such robots can be controlled to achieve diverse types of complex configurations. The first approach consists of approximating the dynamics of the system, including its actuators, as a linear state-space model in order to apply optimal robust control techniques such as H∞ state-feedback and H∞ output-feedback methods. These techniques are designed to utilize the decentralized control structure of the robot and its distributed sensing and actuation to achieve vibration control and trajectory tracking. The approach is validated in simulation on an Euler-Bernoulli dynamic model of a hydrogel based cantilevered robotic arm and in experiments with a hydrogel-actuated miniature 2-DOF manipulator. The second approach is developed for soft continuum robots with dynamics that can be modeled using Cosserat rod theory. An inverse dynamics control approach is implemented on the Cosserat model of the robot for tracking configurations that include bending, torsion, shear, and extension deformations. The decentralized controller structure facilitates its implementation on robot arms composed of independently-controllable segments that have local sensing and actuation. This approach is validated on simulated 3D robot arms and on an actual silicone robot arm with distributed pneumatic actuation, for which the inverse dynamics problem is solved in simulation and the computed control outputs are applied to the robot in real-time.
ContributorsDoroudchi, Azadeh (Author) / Berman, Spring (Thesis advisor) / Tsakalis, Konstantinos (Committee member) / Si, Jennie (Committee member) / Marvi, Hamid (Committee member) / Arizona State University (Publisher)
Created2022
Description
Technological progress in robot sensing, design, and fabrication, and the availability of open source software frameworks such as the Robot Operating System (ROS), are advancing the applications of swarm robotics from toy problems to real-world tasks such as surveillance, precision agriculture, search-and-rescue, and infrastructure inspection. These applications will require the development of robot controllers and system architectures that scale well with the number of robots and that are robust to robot errors and failures. To achieve this, one approach is to design decentralized robot control policies that require only local sensing and local, ad-hoc communication. In particular, stochastic control policies can be designed that are agnostic to individual robot identities and do not require a priori information about the environment or sophisticated computation, sensing, navigation, or communication capabilities. This dissertation presents novel swarm control strategies with these properties for detecting and mapping static targets, which represent features of interest, in an
unknown, bounded, obstacle-free environment. The robots move on a finite spatial grid according to
the time-homogeneous transition probabilities of a Discrete-Time Discrete-State (DTDS) Markov chain model, and they exchange information with other robots within their communication range using a consensus (agreement) protocol. This dissertation extend theoretical guarantees on multi-robot consensus over fixed and time-varying communication networks with known connectivity properties to consensus over the networks that have Markovian switching dynamics and no presumed connectivity. This dissertation develops such swarm consensus strategies for detecting a single feature in the environment, tracking multiple features, and reconstructing a discrete distribution of features modeled as an occupancy grid map.
The proposed consensus approaches are validated in numerical simulations and in 3D physics-based simulations of quadrotors in Gazebo. The scalability of the proposed approaches is examined through extensive numerical simulation studies over different swarm populations and environment sizes.
ContributorsShirsat, Aniket (Author) / Berman, Spring (Thesis advisor) / Lee, Hyunglae (Committee member) / Marvi, Hamid (Committee member) / Saripalli, Srikanth (Committee member) / Gharavi, Lance (Committee member) / Arizona State University (Publisher)
Created2022
Description
Autonomous Robots have a tremendous potential to assist humans in environmental monitoring tasks. In order to generate meaningful data for humans to analyze, the robots need to collect accurate data and develop reliable representation of the environment. This is achieved by employing scalable and robust navigation and mapping algorithms that facilitate acquiring and understanding data collected from the array of on-board sensors. To this end, this thesis presents navigation and mapping algorithms for autonomous robots that can enable robot navigation in complexenvironments and develop real time semantic map of the environment respectively. The first part of the thesis presents a novel navigation algorithm for an autonomous underwater vehicle that can maintain a fixed distance from the coral terrain while following a human diver. Following a human diver ensures that the robot would visit all important sites in the coral reef while maintaining a constant distance from the terrain reduces heterscedasticity in the measurements. This algorithm was tested on three different synthetic terrains including a real model of a coral reef in Hawaii. The second part of the thesis presents a dense semantic surfel mapping technique based on top of a popular surfel mapping algorithm that can generate meaningful maps in real time. A semantic mask from a depth aligned RGB-D camera was used to assign labels
to the surfels which were then probabilistically updated with multiple measurements. The mapping algorithm was tested with simulated data from an RGB-D camera and the results were analyzed.
ContributorsAntervedi, Lakshmi Gana Prasad (Author) / Das, Jnaneshwar (Thesis advisor) / Martin, Roberta E (Committee member) / Marvi, Hamid (Committee member) / Arizona State University (Publisher)
Created2021
Description
The unparalleled motion and manipulation abilities of an octopus have intrigued engineers and biologists for many years. How can an octopus having no bones transform its arms from a soft state to a one stiff enough to catch and even kill prey? The octopus arm is a muscular hydrostat that enables these manipulations in and through its arm. The arm is a tightly packed array of muscle groups namely longitudinal, transverse and oblique. The orientation of these muscle fibers aids the octopus in achieving core movements like shortening, bending, twisting and elongation as hypothesized previously. Through localized electromyography (EMG) recordings of the longitudinal and transverse muscles of Octopus bimaculoides quantitatively the roles of these muscle layers will be confirmed. Five EMG electrode probes were inserted into the longitudinal and transverse muscle layers of an amputated octopus arm. One into the axial nerve cord to electrically stimulate the arm for movements. The experiments were conducted with the amputated arm submerged in sea water with surrounded cameras to record the movement, all housed in a Faraday cage. The findings of this research could possibly lead to the development of soft actuators built out of soft materials for applications in minimally invasive surgery, search-and-rescue operations, and wearable prosthetics.
ContributorsMathews, Robin Koshy (Author) / Marvi, Hamid (Thesis advisor) / Fisher, Rebecca (Committee member) / Xu, Zhe (Committee member) / Arizona State University (Publisher)
Created2022