Robotics Commons^™

Sam-1: An Assistive Robot For Remote Patient Monitoring, Aana Farhana Ahsan

USF Tampa Graduate Theses and Dissertations

The global aging population has increased the demand for caregiving, while the availability of caregivers has not grown at the same pace. These trends have contributed to disparities in consistent and accessible care for older adults and increased caregiver burden. Geriatric care robots have emerged as a promising solution to support older adults and reduce caregiver burden. Existing systems have been developed for a wide range of applications, including rehabilitation, social support, assistance with activities of daily living, therapy, and caregiver telepresence. This thesis presents the development of SAM-1, an assistive robot designed to support remote monitoring of older adults …

Bridging Virtual Robots And Physical Tasks Via Augmented Reality, Xiangfei Kong

USF Tampa Graduate Theses and Dissertations

Entry to human-robot interaction research, e.g., conducting empirical experiments, faces a significant economic barrier due to the high cost of physical robots, ranging from thousands to tens of thousands. This cost issue also severely limits the field’s ability to replicate user studies and reproduce the results to verify their reliability, thus offering more confidence to incorporate these findings. Although virtual reality (VR) user studies present a potential solution, it is unclear whether we can confidently transfer the findings to physical robots and physical environments because VR isolates both the physical robot and the physical world where robots operate. To address …

Robotic Multi-Object Grasping From A Pile: Techniques And Algorithms For Enhanced Dexterity, Tianze Chen

USF Tampa Graduate Theses and Dissertations

As robots become increasingly integrated into real-world applications such as warehousing, fulfillment centers, and manufacturing, the need for efficient and adaptable robotic systems grows. One of the key challenges is enabling robots to grasp multiple objects simultaneously, as this significantly boosts the efficiency of tasks like batch picking, sorting, and object transferring, reducing both time and energy consumption. This dissertation presents a comprehensive multi-object grasping (MOG) pipeline that includes pre-grasp selection, end-pose selection, grasping synergy calculation, and a data-driven model for estimating the number of objects being grasped. Central to this work is the development of the Experience Forest structure, …

Human Motion-Inspired Inverse Kinematics Algorithm For A Robotics-Based Human Upper Body Model, Urvish Trivedi

USF Tampa Graduate Theses and Dissertations

The goal of this research is to develop a human motion-inspired inverse kinematics algorithm framework specifically designed for a Robotics-Based Human Upper Body Model (RHUBM). This framework offers solutions to challenges in various fields. In humanoid robotics, the framework addresses the problem of unnatural robot movement by enabling the development of motion planning algorithms that incorporate human-like movements. For prosthetics, the framework tackles the challenge of amputee difficulty in learning and controlling prosthetics by providing a user-friendly interface that predicts and visualizes upper limb movements, enabling learning and practice. In rehabilitation therapy, the framework tackles …

Under Pressure: The Soft Robotic Clap-And-Fling Of Cuvierina Atlantica, Daniel Mead

USF Tampa Graduate Theses and Dissertations

Evolution over billions of years has led to unique animals of all types. The tiny sea butterfly is one that remains mostly anonymous because of its size and low place on the food chain, but it is a swimming creature that when examined closely reveals a surprise. Shockingly, it has a swimming motion nearly identical to small insects flying at intermediate Reynolds numbers, referred to as the clap-and-fling. The centimeter long pteropod flapping briskly at 5Hz escapes attention with its size and speed. Modeling the clap-and-fling motion of the sea butterfly at a larger scale allows the benefits and uniqueness …

Brain-Inspired Spatio-Temporal Learning With Application To Robotics, Thiago André Ferreira Medeiros

USF Tampa Graduate Theses and Dissertations

The human brain still has many mysteries and one of them is how it encodes information. The following study intends to unravel at least one such mechanism. For this it will be demonstrated how a set of specialized neurons may use spatial and temporal information to encode information. These neurons, called Place Cells, become active when the animal enters a place in the environment, allowing it to build a cognitive map of the environment. In a recent paper by Scleidorovich et al. in 2022, it was demonstrated that it was possible to differentiate between two sequences of activations of a …

Only Pick Once-Multi-Object Picking Algorithms For Picking Exact Number Of Objects Efficiently, Zihe Ye

USF Tampa Graduate Theses and Dissertations

Picking up multiple objects at once is a grasping skill that makes a human worker efficient in many domains. However, the State of Arts Robot Grasping skill has not developed such ability to compete with human.This paper presents a system to pick a requested number of objects by only picking once (OPO). The proposed Only-Pick-Once System (OPOS) contains several graph-based algorithms that convert the layout of objects into a graph, cluster nodes in the graph, rank and select candidate clusters based on their topology. OPOS also has a multi-object picking predictor based on a convolutional neural network for estimating how …

Robot Learning To Pour Solid Objects Accurately, Juan Wilches, Yu Sun

Florida Conference on Recent Advances in Robotics

Pouring is an efficient way to transfer objects from
one container to another. This abstract summarizes a method
to accurately pour solid objects, such as ice cubes. It leverages
visual and proprioceptive feedback together with contextual
information to control the forward and backward rotation of the
pouring container. These feedback signals are fed to a recurrent
neural network that produces the control signal. The proposed
approach can achieve a human-like pouring accuracy in both a
simulation and a real setup.

Multi-Object Grasping -- Stochastic Grasping From A Pile, Tianze Chen, Adheesh Shenoy, Yu Sun

Florida Conference on Recent Advances in Robotics

Grasping multiple objects at once from a pile is common for humans. It makes us efficient in pick and transfer tasks. It is essential for a robot to gain multi-object grasping capability (MOG). This paper defines the multi-object grasping problem and introduces several novel multi-object grasping techniques. These techniques include probability-based pre-grasp potential calculation, a stochastic flexing/extending routine, obtaining end-grasp types, and estimating the number of objects in a grasp. It also proposes a new stochastic grasping strategy for grasping a desired number of objects.

Live Audiovisual Remote Assistance System (Laras) For Person With Visual Impairments, Zachary Frey, Nghia Vo, Varaha Maithreya, Tais Mota, Urvish Trivedi, Redwan Alqasemi, Rajiv Dubey

Florida Conference on Recent Advances in Robotics

According to "The World Report on Vision" by World Health Organization (WHO) [1], there are more than 2.2 billion people who have near or distant vision Impairments, out of which 36 million people are classified as entirely blind. This report also emphasizes the importance of social and communal support in enabling individuals with vision impairments to integrate into society and reach their full potential. While performing daily activities and navigating the environment, people with visual impairments (PVIs) often require direct or synchronous assistance [2]. Consequently, there is a growing need for automated solutions to assist in this regard. However, existing …

Assistive Robotic Platform For Non‐Urgent Household Tasks: A New Design, Amanda Serger, Normandy Tanguilan, Hakki Erhan Sevil

Florida Conference on Recent Advances in Robotics

Humans overcome minor household inconveniences daily without fully recognizing how challenging these tasks could be for individuals such as elderly people or people with disabilities. Those people often times struggle to complete tasks, for instance opening a door or reaching for an item, leading them to rely on caregivers for help. During the COVID-19 pandemic, this caregiver support becomes an unsafe and unreliable solution that can result in a greater risk, thus the need for another solution arises: robotic technology. Recent developments in the robotics field have paved the way for this research, aiming to design a home assistance robot …

Reinforcement Learning And Place Cell Replay In Spatial Navigation, Chance Hamilton, Pablo Scleidorovich Phd, Alfredo Weitzenfeld Phd

Florida Conference on Recent Advances in Robotics

In the last decade, studies have demonstrated that hippocampal place cells influence rats’ navigational learning ability. Moreover, researchers have observed that place cell sequences associated with routes leading to a reward are reactivated during rest periods. This phenomenon is known as Hippocampal Replay, which is thought to aid navigational learning and memory consolidation. These findings in neuroscience have inspired new robot navigation models that emulate the learning process of mammals. This study presents a novel model that encodes path information using place cell connections formed during online navigation. Our model employs these connections to generate sequences of
state-action pairs to …

Biologically Inspired Multi-Robot System Based On Wolf Hunting Behavior, Zachary Hinnen, Chance Hamilton, Alfredo Weitzenfeld

Florida Conference on Recent Advances in Robotics

Studies involving the group predator behavior of wolves have inspired multiple robotic architectures to mimic these biological behaviors in their designs and research. In this work, we aim to use robotic systems to mimic wolf packs' single and group behavior. This work aims to extend the original research by Weitzenfeld et al [7] and evaluate under a new multi-robot robot system architecture. The multiple robot architecture includes a 'Prey' pursued by a wolf pack consisting of an 'Alpha' and 'Beta' robotic group. The Alpha Wolf' will be the group leader, searching and tracking the 'Prey.' At the same time, the …

Programming By Demonstration Using Learning Based Approach: A Mini Review, Atul Acharya, Rajiv Dubey, Redwan Alqasemi

Florida Conference on Recent Advances in Robotics

Wheelchair-mounted robotic arms are used in rehabilitation robotics to help physically impaired people perform ADL (Activity of daily living) tasks. However, the dexterity of manipulation tasks makes the teleoperation of the robotic arm challenging for the user, as it is difficult to control all degrees of freedom with a handheld joystick or a screen touch device. PbD (Programming by demonstration) allows the user to demonstrate the desired behavior and enables the system to learn from the demonstrations and adapt to a new environment. This learned model can perform a new set of actions in a new environment. Learning from a …

A Human-In-The-Loop Robot Grasping System With Grasp Quality Refinement, Tian Tan

USF Tampa Graduate Theses and Dissertations

The goal of this dissertation is to develop a grasping system for assistive robots that can help people with disabilities and the elderly to perform tasks of daily living. In developing this robot grasping system, we maximize its reliability, accuracy, and autonomy. High reliability and accuracy are required for robots to perform tasks around human users and to safely interact with objects that might be fragile or have contents that could spill. High autonomy is desired as users with disabilities are usually not dexterous enough to directly operate the robot. In this dissertation, a human-in-the-loop (HitL) robot grasping system is …

Process Automation And Robotics Engineering For Industrial Processing Systems, Drake Stimpson

USF Tampa Graduate Theses and Dissertations

Automation in industrial systems applications has emerged as the fundamental solution for improving quality, production rate, and efficiency of a process. Much of the recent popularity surrounding the transition of processes from manually operated tasks to automated systems can be attributed to the concept of Industry 4.0, which outlines the fundamental guidelines for integrating cyber-physical systems into industrial processes. Due to rapid advancement of technology in robotics and automation as well as the increase in accessibility of resources to this technology, the capability to develop automated systems has become feasible for small-scale enterprise. This work presents a two-part initiative to …

Adaptive Multi-Scale Place Cell Representations And Replay For Spatial Navigation And Learning In Autonomous Robots, Pablo Scleidorovich

USF Tampa Graduate Theses and Dissertations

Place cells are one of the most widely studied neurons thought to play a vital role in spatial cognition. Extensive studies show that their activity in the rodent hippocampus is highly correlated with the animal’s spatial location, forming “place fields” of smaller sizes near the dorsal pole and larger sizes near the ventral pole. Despite advances, it is yet unclear how this multi-scale representation enables navigation in complex environments.

In this dissertation, we analyze the place cell representation from a computational point of view, evaluating how multi-scale place fields impact navigation in large and cluttered environments. The objectives are to …

Analyzing Decision-Making In Robot Soccer For Attacking Behaviors, Justin Rodney

USF Tampa Graduate Theses and Dissertations

In robotics soccer, decision-making is critical to the performance of a team’s SoftwareSystem. The University of South Florida’s (USF) RoboBulls team implements behavior for the robots by using traditional methods such as analytical geometry to path plan and determine whether an action should be taken. In recent works, Machine Learning (ML) and Reinforcement Learning (RL) techniques have been used to calculate the probability of success for a pass or goal, and even train models for performing low-level skills such as traveling towards a ball and shooting it towards the goal[1, 2]. Open-source frameworks have been created for training Reinforcement Learning …

Humanoid Robot Motion Control For Ramps And Stairs, Tommy Truong

USF Tampa Graduate Theses and Dissertations

Humanoid robot research and development have been an ongoing effort since the 1900sand can be broken down to two problems. A mechanical problem, getting a humanoid robot to move human-like or a software problem, getting a humanoid robot to behave human-like. These problems of moving and behaving human-like can be often solved using control theory as research advances. For the premise of this research, we explore how to balance and walk on non-flat terrain for the humanoid robot Darwin-Op. Since the focus was on the control theory, the vision control to detect the non-flat terrain was a side objective. The …

Learning State-Dependent Sensor Measurement Models To Improve Robot Localization Accuracy, Troi André Williams

USF Tampa Graduate Theses and Dissertations

This dissertation proposes a novel method called state-dependent sensor measurement models (SDSMMs). Such models dynamically predict the state-dependent bias and uncertainty of sensor measurements, ultimately improving fundamental robot tasks such as localization. In our first investigation, we introduced the state-dependent sensor measurement model framework, described their properties, stated the input and output of these models, and described how to train them. We also explained how to integrate such models with an Extended Kalman Filter and a Particle Filter, two popular robot state estimation algorithms. We validated the proposed framework through a series of localization tasks. The results showed that our …

Trilateration-Based Localization In Known Environments With Object Detection, Valeria M. Salas Pacheco

USF Tampa Graduate Theses and Dissertations

Many strategies for localization have been proposed, the majority of which rely on distance calculations and estimates. The proposed approach is a method that combines image-based single-camera localization techniques and the principle of trilateration to perform localization in a known indoor environment. By using a camera, the proposed system can detect custom objects using object detection in an indoor environment and calculate an approximation of the camera’s position. To recognize the location, previous information such as the size of the environment and the coordinates and sizes of the objects in the environment are given as input to the system together …

Design And Implementation Of Intuitive Human-Robot Teleoperation Interfaces, Lei Wu

USF Tampa Graduate Theses and Dissertations

We have designed and implemented a novel human-robot teleoperation interface based on an intuitive reference frame and hybrid inverse kinematics to perform activities of daily living(ADL) using multiple input devices.

Persons with disabilities often rely on caregivers or family members to assist in their daily living activities. Providing robotic assistants with easy and intuitive user interfaces to assist with ADL can improve their quality of life and lift some of the burdens on caregivers and family members. Current human-robot interface solutions, such as joysticks, Kinect based gesture recognition, and touchscreen-based solutions, including smartphones, are still far from being able to …

Roboat - Rescue Operations Bot Operating In All Terrains, Akshay Gulhane

USF Tampa Graduate Theses and Dissertations

Natural calamities are on a rise with each passing year. Disasters like floods and fire take many lives all around the world, especially in remote areas or less developed countries. One such incident was the Kerala Floods in India where rescue services had difficulty reaching to all the people on time since a huge landmass (more than 9 districts) was flooded and hence villagers or other people risked their lives to save others in danger without proper safety equipment. Amazon Rainforest Fires was another example for a major destruction of an ecosystem. The main reason for lack of facilities in …

Control Of A Human Arm Robotic Unit Using Augmented Reality And Optimized Kinematics, Carlo Canezo

USF Tampa Graduate Theses and Dissertations

There are more than 350000 amputees in the US who suffer loss of functionality in their daily living activities, and roughly 100000 of them are upper arm amputees. Many of these amputees use prostheses to compensate part of their lost arm function, including power prostheses. Research on 6-7 degree of freedom powered prostheses is still relatively new, and most commercially available powered prostheses are typically limited to 1 to 3 degrees of freedom. Due to the myriad of possible options for various powered protheses from different manufacturers, each configuration is governed by a distinct control scheme typically specific to the …

Action Recognition Using The Motion Taxonomy, Maxat Alibayev

USF Tampa Graduate Theses and Dissertations

In the last years, modern action recognition frameworks with deep architectures have achieved impressive results on the large-scale activity datasets. All state-of-the-art models share one common attribute: two-stream architectures. One deep model takes RGB frames, while the other model is fed with pre-computed optical flow vectors. The outputs of both models are combined to be used as a final probability distribution for the action classes. When comparing the results of individual models with the fused model, it is common to see that that latter method is more superior. Researchers explain that phenomena with the fact that optical flow vectors serve …

Functional Object-Oriented Network: A Knowledge Representation For Service Robotics, David Andrés Paulius Ramos

USF Tampa Graduate Theses and Dissertations

In this dissertation, we discuss our work behind the development of the functional object-oriented network (abbreviated as FOON), a graphical knowledge representation for robotic manipulation and understanding of its own actions and (potentially) the intentions of humans in the household. Based on the theory of affordance, this representation captures manipulations and their effects on actions through the coupling of object and motion nodes as fundamental learning units known as functional units. The activities currently represented in FOON are cooking related, but this representation can be extended to other activities that involve manipulation of objects which result in observable changes of …

Design Of Delro Autonomous Delivery Robot And Ai Based Localization, Tolga Karakurt

USF Tampa Graduate Theses and Dissertations

Autonomous robots are employed in numerous areas. In this thesis, it is proposed to design and build a self-controlled wheeled vehicle to deliver food.

As there are many applications of an autonomous agent for indoor and outdoor environments, this study is conducted on indoor settings whereas all the requirements and design processes are achieved for both operational boundaries.

The fundamental approach is to design and implement a Wheeled Mobile Robot (WMR), and to test skid-steering performance on proposed trajectories using a System Engineering approach. From this point of view, system requirements in mechanical, electrical, and software are evaluated, and overall …

The Design And Development Of A Wrist-Hand Orthosis, Amber Gatto

USF Tampa Graduate Theses and Dissertations

Individuals with an incomplete C5-C7 spinal cord injury (SCI) lose grasping abilities but wrist function is almost universally retained. Most rehabilitation techniques apply the tenodesis effect, however, current tenodesis wrist-hand orthoses (WHOs) engage only the thumb and index finger, meaning that only 20% of activities of daily living (ADLs) can be completed.

This study tested the feasibility of a student-designed powered WHO by testing the device on healthy subjects to see if they could complete a variety of ADLs. A simulation software was then used to analyze wrist, thumb, and index finger joint angles. Additionally, an Assistive Technology Survey was …

Distributed Spatiotemporal Control And Dynamic Information Fusion For Multiagent Systems, Dzung Minh Duc Tran

USF Tampa Graduate Theses and Dissertations

The first objective of this dissertation is to develop novel distributed control architectures allowing spatiotemporal control of multiagent systems as applied to formation control. In addition, its second objective is to introduce distributed estimation frameworks for dynamic information fusion for addressing the heterogeneity in sensor networks.

Changing the spatial and temporal properties of agent teams in a distributed manner and in real-time is an open problem in the control system literature as multiagent systems are often required to complete tasks with ever-increasing complexity in adverse conditions and dynamic environments. Motivated by this standpoint, this dissertation aims to address challenges related …

Robotic Motion Generation By Using Spatial-Temporal Patterns From Human Demonstrations, Yongqiang Huang

USF Tampa Graduate Theses and Dissertations

Robots excel in manufacturing facilities because the tasks are repetitive and do not change. However, when the tasks change, which happens in almost all tasks that humans perform daily, such as cutting, pouring, and grasping, etc., robots perform much worse. We aim at teaching robots to perform tasks that are subject to change using demonstrations collected from humans, a problem referred to as learning from demonstration (LfD).

LfD consists of two parts: the data of human demonstrations, and the algorithm that extracts knowledge from the data to perform the same motions. Similarly, this thesis is divided into two parts. The …