With the advancement in technology, modern autonomous vehicles are required to perform more complex tasks and navigate through challenging terrains. Thus, the amount of computation resources to accurately accomplish those tasks have exponentially grown in the last decade. With growing computational intensity and limited computational resources on embedded devices, schedulers are necessary to manage and fully optimize computational loads between the GPU and CPU as well as reducing the power consumption to maximize time in the field. Thus far, it has been proven the effectiveness of schedulers and path planners on computational load on embedded devices through numerous bench testing and simulated environments. However, there have not been any significant data collection in the real-world with all hardware and software combined. This thesis focuses on the implementation of various computational loads (i.e. scheduler, path planner, RGB-D camera, object detection, depth estimation, etc.) on the NVIDIA Jetson AGX Xavier and real-world experimentation on the Clearpath Robotics Jackal. We compare the computation response time and effectiveness of all systems tested in the real-world versus the same software and hardware architecture on the bench. / Master of Science / Modern autonomous vehicles are required to perform more complex tasks with limited computational resources, power and operating frequency. In recent past, the research around autonomous vehicles have been focused on proving the effectiveness of using software-based programming on embedded devices with integrated GPU to improve the overall performance by speeding up task completion. Our goal is to perform real-world data collection and experimentation with both hardware and software frameworks onboard the Clearpath Robotics Jackal. This will validate the efficiency and computational load of the software framework under multiple varying environments.

<p dir="ltr">The research study of Design and Modeling of a Balloon Robot with Wheel Paddles for Agricultural Use (Huang, et al. 2023) presented the design, analysis, and simulation of an innovative agricultural robot that integrated a buoyancy system with a helium balloon and wheeled paddles for navigation, aiming to optimize crop health monitoring. The thesis research initiated with a comprehensive examination of the conceptual design, focusing on the robot's buoyancy mechanism and propulsion system. Detailed motion analysis and kinematic studies underpinned the development of a dynamic model, which was rigorously tested through MATLAB simulations. The MATLAB simulations assessed the unmanned vehicle's operational efficiency, maneuverability, and energy consumption in the environment setting of agricultural. The findings of the new design highlighted the robot's potential to surpass traditional agricultural robots in precision and adaptability, mitigating the limitations of ground and aerial alternatives. The thesis study of the balloon robot concluded with strategic recommendations for future enhancements, emphasizing scalability, payload capacity, and environmental adaptability, thus paving the way for advanced agricultural robotics.</p>

This thesis addresses two important issues when operating the novel three legged mobile robot STriDER (Self-excited Tripedal Dynamic Experimental Robot); how to stand up after falling down while minimizing the motor torques at the joints and considerations for gait planning. STriDER uses a unique tripedal gait to walk with high energy efficiency and has the ability to change directions. In the first version of STriDER, the concept of passive dynamic locomotion was emphasized; however, for the new version, all joints are actively controlled for robustness. The robot is inherently stable when all three feet are on the ground due to its tripod stance, but it can still fall down if it trips while taking a step or if unexpected external forces act on it. The unique structure of STriDER makes the simple task of standing up challenging for a number of reasons; the high height of the robot and long limbs require high torque at the actuators due to its large moment arms; the joint configuration and length of the limbs limit the workspace where the feet can be placed on the ground for support; the compact design of the joints allows limited joint actuation motor output torque; three limbs do not allow extra support and stability in the process of standing up. This creates a unique problem and requires novel strategies to make STriDER stand up. This thesis examines five standing up strategies unique to STriDER: three feet pushup, two feet pushup, one foot pushup, spiral pushup, and feet slipping pushup. Each strategy was analyzed and evaluated considering constraints such as static stability, friction at the feet, kinematic configuration and joint motor torque limits to determine optimal design and operation parameters. Using the findings from the analysis, experiments were conducted for all five standing up strategies to determine the most efficient standing up strategy for a given prototype using the same design and operation parameters for each method. Also, a literature review was conducted for human standing from a chair and human pushup exercises and the conclusions were compared to the analysis presented in this thesis. Many factors contribute to the development of STriDER's gait. Several considerations for gait planning as the robot takes a step are investigated, including: stability, dynamics, the body's maximum and minimum allowable heights, the swing legs foot clearance to the ground, and the range of the subsequent swing foot contact positions. A static stability margin was also developed to asses the stability of STriDER. This work will lay the foundation for future gait generation research for STriDER. Additionally, guidelines for future work on single step gait generation based on kinematics and dynamics are discussed. The findings presented will advance the capabilities and adaptability of the novel robot STriDER. By studying standing up strategies and gait planning issues, the most efficient control methods can be implement for standing up and preparing to take a step and lay out the foundations for future research and development on STriDER. / Master of Science

The growing presence of modern learning robots necessitates a fundamental shift in design, as these robots must learn skills from human inputs. Two main components close the loop in a human-robot interaction: learning and communication. Learning derives robot behaviors from human inputs, and communication conveys information about the robot's learning to the human. This dissertation focuses on methods that enable robots to communicate their internal state clearly while learning precisely from human inputs. We first consider the information implicitly communicated by robot behavior during human interactions and whether it can be utilized to form human-robot teams. We investigate behavioral economics to identify biases and expectations in human team dynamics and incorporate them into human-robot teams. We develop and demonstrate an optimization approach that relates high-level subtask allocations to low-level robot actions, which implicitly communicates learning to encourage human participation in robot teams. We then study how communication helps humans teach tasks to robots using active learning and interactive imitation learning algorithms. Within the active learning approach, we develop a model that forms a belief over the human's mental model about the robot's learning. We validate that our algorithm enables the robot to balance between learning human preferences and implicitly communicating its learning through questions. Within the imitation learning approach, we integrate a wrapped haptic display that explicitly communicates representations from the robot's learned behavior to the user. We show that our framework helps the human teacher improve different aspects of the robot's learning during kinesthetic teaching. We then extend this system to a more comprehensive interactive learning architecture that provides multi-modal feedback through augmented reality and haptic interfaces. We present a case study with this closed-loop system and illustrate improved teaching, trust, and co-adaptation as the measured benefits of communicating robot learning. Overall, this dissertation demonstrates that bi-directional communication helps robots learn faster and adapt better, while humans experience a more intuitive and trust-based interaction. / Doctor of Philosophy / The growing presence of modern learning robots necessitates a fundamental shift in design, as these robots must learn skills from human inputs. This dissertation focuses on methods that enable robots to communicate their internal state clearly while learning precisely from human inputs. We first consider how robot behaviors during human interactions can be used to form human-robot teams. We investigate human-human teams in behavioral economics to better understand human expectations in human-robot teams. We develop a model that enables robots to distribute subtasks in a way that encourages their human partner to keep collaborating with them. We then study how communication helps human-in-the-loop robot teaching. Within active learning, we develop a model that infers what the human thinks about the robot's learning. We validate that, with our algorithm, the robot efficiently learns human preferences and keeps the human updated about what it has learned. Within imitation learning, we integrate a haptic device that explicitly communicates features from the robot's learned behavior to the user. We show that our framework helps users effectively improve their kinesthetic teaching. We then extend this system to a more comprehensive interactive robot learning architecture that provides feedback through augmented reality and haptic interfaces. We conduct a case study and illustrate that our framework improves robot teaching, human trust, and human-robot co-adaptation. Overall, this dissertation demonstrates that bi-directional communication helps robots learn faster and adapt better, while humans experience a more intuitive and trust-based interaction.

A unique modular snake-like robotic arm, also referred to as MA\RS – the Modular Arm \ Robotic System - was designed, manufactured, assembled, simulated, and programmed to create a modular robot which could move to a desired end position given the number of links, the position of the end link and the duration of motion. This robotic arm serves as the start of research into a modular space robotic system to be used in low-gravity environments. As such, this project focused on developing the initial design of the robot and its digital twin. The system’s modularity allows for changes to the robot’s workspace, which allow for the accomplishment of different tasks. The modular aspect of the robot required strong and lightweight links and used a bent sheet metal assembly to reduce mass and conserve strength. Each of the robot’s links used a custom-built PCB to power the system, send signals from the MCU (an ESP32-S2) to the motor, and communicate to the main controller using CAN Bus. Simulation of the robot was performed using a MATLAB script and GUI built in MATLAB’s App Designer, which calculated the system’s path planning and inverse kinematics. The GUI communicated with the robot (through serial) and controlled the robot’s motion as it was calibrated and moved from one location to another.

Robot assisted therapy is becoming increasingly popular. Research has proven it can be of benefit to persons dealing with a variety of disorders, such as Autism Spectrum Disorder (ASD), Attention Deficit Hyperactivity Disorder (ADHD), and it can also provide a source of emotional support e.g. to persons living in seniors’ residences. The advancement in technology and a decrease in cost of products related to consumer electronics, computing and communication has enabled the development of more advanced social robots at a lower cost. This brings us closer to developing such tools at a price that makes them affordable to lower income individuals and families. Currently, in several cases, intensive treatment for patients with certain disorders (to the level of becoming effective) is practically not possible through the public health system due to resource limitations and a large existing backlog. Pursuing treatment through the private sector is expensive and unattainable for those with a lower income, placing them at a disadvantage. Design and effective integration of technology, such as using social robots in treatment, reduces the cost considerably, potentially making it financially accessible to lower income individuals and families in need. The Objective of the research reported in this manuscript is to design and implement a social robot that meets the low-cost criteria, while also containing the required functions to support children with ASD. The design considered contains knowledge acquired in the past through research involving the use of various types of technology for the treatment of mental and/or emotional disabilities.

The emergence of cloud computing has transformed the potential of robotics by enabling multi-robotic teams to fulfil complex tasks in the cloud. This paradigm is known as “cloud robotics” and relieves robots from hardware and software limitations, as large amounts of available resources and parallel computing capabilities are available in the cloud. The introduction of cloud-enabled robots alleviates the need for computationally intensive robots to be built, as many, if not all, of the CPU-intensive tasks can be offloaded into the cloud, resulting in multi-robots that require much less power, energy consumption and on-board processing units. While the benefits of cloud robotics are clearly evident and have resulted in an increase in interest among the scientific community, one of the biggest challenges of cloud robotics is the inherent communication challenges brought about by disconnections between the multi-robotic system and the cloud. The communication delays brought about by the cloud disconnection results in robots not being able to receive and transmit data to the physical cloud. The unavailability of these robotic services in certain instances could prove fatal in a heterogeneous environment that requires multi-robotic teams to assist with the saving of human lives. This niche area is relatively unexplored in the literature. This work serves to assist with the challenge of disconnection in cloud robotics by proposing a survivable cloud multi-robotics (SCMR) framework for heterogeneous environments. The SCMR framework leverages the combination of a virtual ad hoc network formed by the robot-to-robot communication and a physical cloud infrastructure formed by the robot-to-cloud communications. The Quality of Service (QoS) on the SCMR framework is tested and validated by determining the optimal energy utilization and Time of Response (ToR) on drivability analysis with and without cloud connection. The experimental results demonstrate that the proposed framework is feasible for current multi-robotic applications and shows the survivability aspect of the framework in instances of cloud disconnection. / School of Computing / M.Sc. (Computer Science)

Thesis (MScEng)--Stellenbosch University, 2011. / ENGLISH ABSTRACT: RoboCup promotes research in robotics and multi-robot systems (MRS). The RoboCup Small Size League (SSL), in particular, offers an entry level opportunity to take part in this field of study. This thesis presents a starting phase for research in robotics and MRS at Stellenbosch University. It includes the full documentation of the mechanical, electronic and software design of an omni-directional soccer robot for RoboCup SSL. The robot is also meant to operate as a hardware and software development platform for research in MRS. The platform was therefore designed with high-level programming language compatibility, a wide range of connectivity, and modularity in mind. The robot uses a single board computer (SBC) running a Linux operating system to accomplish these objectives. Moreover, a driver class library was written in C++ as a software application interface (API) for future development on the robot platform. The robot was also developed with a particular focus on a distributed control architecture. "Player" was implemented as the middleware, which can be used for communication between multiple robots in a distributed environment. Additionally, three tests were performed to demonstrate the functionality of the prototype: a PI speed control test, a direction accuracy test and a static communication test using the middleware. Recommendations for possible future work are also given. / AFRIKAANSE OPSOMMING: RoboCup bevorder navorsing in robotika en multi-robot-stelsels (MRS). Die RoboCup Klein Liga (KL) bied in die besonder die geleentheid om op intreevlak navorsing te doen in hierdie veld. Hierdie tesis verteenwoordig die eerste fase van navorsing in robotika en MRS by Stellenbosch Universiteit. Dit sluit die volledige dokumentasie van die meganiese, elektroniese en sagteware-ontwerp van ’n omnidireksionele sokker-robot vir die KL in. Die robot is ook veronderstel om te dien as ’n hardeware- en sagteware-ontwikkelingsplatform vir navorsing in MRS. Die platform is dus ontwerp met ’n verskeidenheid van uitbreingsmoontlikhede en modulariteit in gedagte asook die moontlikheid om gebruik te maak van ’n hoë-vlak programmeertaal. Om hierdie doelwitte te bereik, maak die robot gebruik van ’n enkel-bord-rekenaar met ’n Linux bedryfstelsel. Verder was ’n sagteware drywer in C++ geskryf om te dien as ’n sagteware-koppelvlak vir toekomstige ontwikkeling op die robot platform. Die robot is ook ontwikkel met die besondere fokus op ’n gedesentraliseerde beheerstels. Player was geïmplementeer as die middelware, wat gebruik kan word vir kommunikasie tussen verskeie robotte in ’n gedesentralliseerde beheerstelsel. Daar is drie toetse uitgevoer om die funksionaliteit van die prototipe te demonstreer, ’n PI spoed beheer toets, ’n rigting akkuraatheidstoets en ’n statiese kommunikasie toets deur van die middelware gebruik te maak. Aanbevelings vir moontlike toekomstige werk word ook verskaf.

The objective of this research is to develop a framework for multi-robot coordination and control with emphasis on human-swarm and inter-agent interactions. We focus on two problems: in the first we address how to enable a single human operator to externally influence large teams of robots. By directly imposing density functions on the environment, the user is able to abstract away the size of the swarm and manipulate it as a whole, e.g., to achieve specified geometric configurations, or to maneuver it around. In order to pursue this approach, contributions are made to the problem of coverage of time-varying density functions. In the second problem, we address the characterization of inter-agent interactions and enforcement of desired interaction patterns in a provably safe (i.e., collision free) manner, e.g., for achieving rich motion patterns in a shared space, or for mixing of sensor information. We use elements of the braid group, which allows us to symbolically characterize classes of interaction patterns. We further construct a new specification language that allows us to provide rich, temporally-layered specifications to the multi-robot mixing framework, and present algorithms that significantly reduce the search space of specification-satisfying symbols with exactness guarantees. We also synthesize provably safe controllers that generate and track trajectories to satisfy these symbolic inputs. These controllers allow us to find bounds on the amount of safe interactions that can be achieved in a given bounded domain.

Advances in mobile robot technology allow an increasing variety of applications to be imagined, including: search and rescue, exploration of unknown areas and working with hazardous materials. State of the art robots are able to behave autonomously and without direct human control, using on-board devices to perceive, navigate and reason about the world. Unmanned Aerial Vehicles (UAVs) are particularly well suited to performing advanced sensing tasks by moving rapidly through the environment irrespective of the terrain. Deploying groups of mobile robots offers advantages, such as robustness to individual failures and a reduction in task completion time. However, to operate efficiently these teams require specific approaches to enable the individual agents to cooperate. This thesis proposes coordinated approaches to search scenarios for teams of UAVs. The primary application considered is Wilderness Search and Rescue (WiSaR), although the techniques developed are applicable elsewhere. A novel frontier-based search approach is developed for rotor-craft UAVs, taking advantage of available terrain information to minimise altitude changes during flight. This is accompanied by a lightweight coordination mechanism to enable cooperative behaviour with minimal additional overhead. The concept of a team rendezvous is introduced, at which all team members attend to exchange data. This also provides an ideal opportunity to create a comprehensive team solution to relay newly gathered data to a base station. Furthermore, the delay between sensing and the acquired data becoming available to mission commanders is analysed and a technique proposed for adapting the team to meet a latency requirement. These approaches are evaluated and characterised experimentally through simulation. Coordinated frontier search is shown to outperform greedy walk methods, reducing redundant sensing coverage using only a minimal coordination protocol. Combining the search, rendezvous and relay techniques provides a holistic approach to the deployment of UAV teams, meeting mission objectives without extensive pre-configuration.