Doctor of Philosophy, Case Western Reserve University, 2024, EMC - Mechanical Engineering

In robot control, classical stability is formed around a stable point (attractor) or connected stable points (limit cycles). In contrast, connected saddles can be used to describe stable sequences of states. The connection between two saddles in phase space is a heteroclinic channel, and stable heteroclinic channels (SHCs) can be combined to form cycles and networks – stable heteroclinic networks (SHNs). While the stability and subperiod at each saddle have been mathematically predicted, the potential of SHCs as robot controllers has not been fully realized. To move from modelling to control, tools are needed to more precisely design and manipulate these systems. First, this manuscript expands the SHC-framework with a task space transformation inspired by a popular robot control framework – dynamic movement primitives (DMPs). Stable heteroclinic channel-based movement primitives (SMPs) have an intuitive visualization feature that allows users to easily initialize the controller using only the robot's desired trajectory in its task space. After applying SMPs to a simple robotic system, we characterize the SHC system variables in the larger SMP system, and use the SMP variable nu – the saddle value – for local, real-time controller tuning without compromising the overall stability of the system. Finally, we explore more complex, branching connected-saddle topologies as stable heteroclinic networks. SHCs and SHNs are stochastic systems where noisy external input, such as sensory input, can be used as the stochastic component of the system. For robots, we can use SHNs as a decision-making model where the external input directly drives which decision is made. Overall, this manuscript seeks to parametrize the saddle network frameworks SHCs and SHNs for user-friendly, robust, and versatile robot control. Networks of saddles exist as models for neural activity, neuromechanical models, and robot control, and they can provide further utility in the study and application of (open full item for complete abstract)

Master of Sciences (Engineering), Case Western Reserve University, 2024, EMC - Mechanical Engineering

In the interest of studying how jump performance of miniature robots can be improved by changing the initial posture, a 188g grasshopper-inspired jumping robot is built. A cam-driven angle adjustment mechanism allows the robot to jump up to 14% further than without initial posture control. Further testing of alternative robot configurations also found the distance can improve up to 47% when energy loss due to ground impact is mitigated. Using both theoretical trajectories and experimental results, this work demonstrates that angle adjustment can positively affect performance of jumping robots. The design concepts and mechanism discussed in this work may also serve as a reference to future integration of other robots to provide jumping as an additional locomotion method in order to clear obstacles and difficult terrain more efficiently.

PhD, University of Cincinnati, 2024, Engineering and Applied Science: Electrical Engineering

Echolocating bats demonstrate sonar's remarkable ability to support various complex tasks, from navigating dense vegetation to foraging in flight. However, achieving these tasks using echolocation alone presents challenges due to the inherent limitations of sonar. Drawing inspiration from biological systems, we can narrow the performance gap between artificial and biological sonar. In this context, we develop behavior-based systems using sensorimotor loops and their interactions to accomplish the foraging task. We showcase a solution to the foraging task by training machine learning models to arbitrate between the approach and avoid sensorimotor loops using solely echoes as perception inputs. These models demonstrate a high success rate in foraging for insect-like targets and flower targets. In addition, they are robust against different arena geometries, traps, and noisy motor control. While arbitrating between the two sensorimotor loops proves effective, the system does not demonstrate attention to a single target, failing to investigate a flower target thoroughly. To address this, we develop a novel sensorimotor loop, termed the flower home-in loop, designed to guide nectarivorous bats toward a flower opening while maintaining attention on the target. The flower home-in loop perfectly performs when approaching the flower from the front. However, the performance gets worse when approaching the flower from other sides. Continuously re-estimating the target flower pose and updating the bat's path is a more robust strategy for the flower home-in loop in acoustically ambiguous scenarios. The flower home-in loop can also guide the bat toward the echoes from a flower's opening while being interfered with by echoes from nearby objects.

MS, University of Cincinnati, 2024, Engineering and Applied Science: Mechanical Engineering

Testing the free rotation of a satellite in a ground-based laboratory setting presents significant challenges but is essential for the development and validation of a satellite's attitude determination and control system (ADCS). This thesis describes a novel design of a spherical air-bearing based testbed and its control system, specifically engineered for rapid balancing of the floating platform in all three axes for any tested CubeSat, even when the satellite's mass center is unknown. Unlike many other spherical air-bearing testbeds, this design utilizes only three actuators, which is the minimal number of actuators required to achieve quick balancing of the floating top platform across all three rotational axes without prior knowledge of the tested satellite's mass center location. To achieve complete passive rotational balance of a tested satellite, the combined mass center of the floating platform and the satellite must align with the geometric center of the spherical air-bearing. This alignment is challenging due to the unknown mass center of the satellite. A two-step balance control strategy has been developed to achieve the desired balance. The first step involves using Inertial Measurement Unit (IMU) data to move three weights in a coordinated manner, to align the unknown mass center of the floating platform (including the tested CubeSat) to the vertical axis (the Z axis) passing through the rotational center of the spherical air-bearing. A Kalman filter was implemented to process the IMU data, and an acceleration feedback loop provides a quick response to any disturbances causing imbalance. The second step is the vertical, Z-axis alignment. By rapidly moving the actuators in a horizontal direction a disturbance is introduced. This is referred to as a ‘twitch stage.' With the platform moving, the acceleration of the system is then measured during the ‘drift stage.' The results of the drift stage are processed by a proportional–integral–derivative (P (open full item for complete abstract)

Doctor of Philosophy, Case Western Reserve University, 2024, EECS - Electrical Engineering

This thesis presents modeling and control of the magnetically-actuated MRI-guided robotic intravascular cardiac catheter. The robotic catheters are embedded with current carrying coil actuators. The actuator contains one axial coil, and two orthogonal side coils. The catheter is steered by the magnetic moments generated on a set of current carrying actuation coils mounted on the catheter body by the static magnetic feld of an MRI scanner. The kinematics of the robotic catheter is modeled using the Cosserat rod theory as a series of fexible and rigid segments. In the proposed model, the equilibrium confguration of the catheter under external loads, including actuation moments, and the contact force at the tip of the catheter is calculated. A Jacobian-based iterative inverse kinematics and the open-loop control are presented and experimentally validated using hardware setup. This work also presents the model under tip contact position constraint of the MRI-actuated robotic catheter. In this model, the initial value problem parameter derivatives and tip contact force are calculated analytically. The analytical formulation of the relationship between the contact force and the actuation inputs under the tip contact position constraint, described by the contact force Jacobian, is presented. The proposed kinematic model of the MRI-actuated robotic catheter shows very good performance in performing the complex trajectories with high reproducibility during the experiments. These methods deliver consistent performance showing good results in terms of reproducibility and accuracy. This success sets a strong foundation for the potential implementation of a closed-loop control system with real-time MRI guidance information. The simulation based benchmark tests of the proposed analytical method for the calculation of the contact force Jacobian of the MRI-actuated robotic catheter using the Cosserat rod model and the analytical derivations of the IVP parameter derivatives of th (open full item for complete abstract)

Master of Sciences, Case Western Reserve University, 2024, EECS - Computer and Information Sciences

The high positional uncertainty of the surgical robotic manipulator creates a challenge for realizing robust autonomous minimally invasive surgical robots. Their cable-driven mechanism makes it difficult to locate sensors on the end-effector resulting in significant joint angle errors. In this thesis, I present a novel reinforcement learning (RL) approach for error correction based on endoscopic images. By visually tracking multiple keypoints on the end-effector, the RL agent continuously reduces the difference between the estimated and observed poses. This approach demonstrates high robustness to the camera transformation errors and is compared with existing error correction methods using particle filters.

Master of Sciences, Case Western Reserve University, 2024, EECS - Electrical Engineering

This thesis presents the development of an enhanced modular 3-degree-of-freedom (DoF) force sensor integrated with a particle filter, tailored for providing optimized force measurement in robot-assisted minimally invasive surgery (RMIS) researches. The sensor's advanced electromechanical design features an employment of Flexible Printed Circuit Board (FPCB) with Flat Flex Cable (FFC) connectors, alongside novel insert layers between the load cell arrays and the force plate, aiming at an improvement in the robustness with a non-monolithic design. The integration of a particle filter addresses the inaccuracies in joint angles, substantially refining the precision with which forces are resolved into the robot reference frame. Experimental results affirm that this sensor provides fine accuracy of force measurements due to its enhanced design and the integration of the particle filter, suggesting promising avenues for future research, particularly as potential means of providing the ground truth training data for the implementation of supervised machine learning force estimation methods.

MS, Kent State University, 2024, College of Arts and Sciences / Department of Computer Science

Search and rescue missions are critical endeavours aimed at locating survivors trapped in the aftermath of various calamities such as earthquakes, landslides, tsunamis etc. The time efficiency required for these missions is pivotal in saving lives, prompting the adoption of robotics with advanced technology to expedite operations. Effective planning and strategizing play key roles in enhancing a robot's efficiency, particularly in prioritizing areas of need. Typically, search and rescue missions often present a high level of complexity due to a multitude number of factors to be considered when planning and optimizing operations. Factors such as determining hot-spot regions, harsh weather conditions, terrain complexity, environmental hazards, and time sensitivity, just to a mention few, introduce intricacies to the task of effective planning. For instance, a factor such as environmental conditions is considered dynamic as it may change from time to time. Additionally, the criticality of different regions may change dynamically as soon as the information is made available, further complicating the task for both rescue robots and even fast responders. This research addresses the challenge of optimizing path planning in search and rescue missions, treating it as a variant of the travelling salesman problem and proposes a hybrid technique that incorporates both algorithmic and non-algorithmic techniques, to tackle the problem. The hybrid technique leverages a tweaked version of the U-net neural network that is trained on two pieces of information: static data, data that encircles topological map data such as slope and dynamic data deduced from map findings data that would be vital in singling out hotspots and priority regions on the map. Blending these two pieces of information, an amalgamated cost, a value that incorporates both priority and cost of traversal, is determined to aid robot path planning decisions. Training a neural network on this data (open full item for complete abstract)

Master of Computing and Information Systems, Youngstown State University, 2024, Department of Computer Science and Information Systems

The field of coding education is rapidly evolving, with emerging technologies playing a pivotal role in transforming traditional learning methodologies. This thesis introduces Dr. Lego, an innovative framework designed to revolutionize the assessment and understanding of block-based coding through the integration of sophisticated deep learning models. Dr. Lego combines cutting-edge technologies such as MobileNetV3 (Howard, 2019), for visual recognition and BERT (Devlin et al., 2018), and XLNet (Yang et al., 2019) for natural language processing to offer a comprehensive approach to evaluating coding proficiency. The research methodology involves the meticulous curation of a diverse dataset comprising projects from the LEGO SPIKE app (LEGO Education, 2022), ensuring that the models are subjected to a broad range of coding scenarios. Leveraging the dynamic educational environment provided by the LEGO SPIKE app (LEGO Education, 2022), Dr. Lego empowers users to design and implement various coding projects, fostering hands-on learning experiences. This thesis delves into methodologies aimed at enhancing coding education by exploring model integration, data generation, and fine-tuning of pre-trained models. Dr. Lego not only evaluates coding proficiency but also provides cohesive and insightful feedback, enhancing the learning experience for users. The adaptability of the framework highlights its potential to shape the future of coding education, paving the way for a new era of interactive and engaging learning experiences.

Doctor of Philosophy (Ph.D.), University of Dayton, 2024, Mechanical Engineering

This dissertation explores the kinematic synthesis of continuum robots and the design of a specific continuum robot for use in laparoscopy. The kinematic synthesis of continuum robots is studied based on either the desired target end-effector pose or the backbone shape of the robot. Initiating with an investigation into the mathematical relationships among positions and orientations at the segment tips, this study focuses on piecewise constant curvature (PCC) continuum robots with up to three segments. For a continuum robot with more than three segments, a method is introduced for generating the backbone of a continuum robot that closely approximates a given spatial curve. Furthermore, the kinematic synthesis methodology is investigated for designing a chain of three-dimensional bodies to match a set of arbitrary spatial curves. For a one-segment PCC, a reachability criterion is proposed, simplifying the calculation of the neighboring orientation. For a two-segment PCC, a reachability criterion is proposed and the redundancy of its inverse kinematics solution is found, establishing a circle of tip locations. For a three-segment PCC, the redundancy of the inverse kinematics includes tips that lie on a sphere providing a closed-form solution to the inverse kinematics problem. These relationships are derived from the unique characteristics of the bisecting plane of a single segment. The degenerate cases for the solutions are also addressed. These outcomes stem from a specific PCC parametrization, with implications extending to the general PCC model. Note that this study is grounded solely in simulation. Shape-changing mechanisms provide the theoretical tools for the synthesis of spatial chains of rigid bodies that position themselves along curves of any complexity. This study investigates the kinematic synthesis methodology for designing a chain of three-dimensional bodies to match a set of arbitrary spatial curves. The bodies synthesized can be one of three type (open full item for complete abstract)

Master of Science in Electrical Engineering, University of Dayton, 2024, Electrical Engineering

This thesis presents a novel method to control an industrial robotic arm using multiple sensors. This system consists of a hybrid brain activity and vision sensors that convey a human being's intention and visual perception. We fuse and analyze the data from those sensors using a machine learning-based approach to automatically guide the manipulator to a designated location. We believe that this Brain–Machine–Interface (BMI) can greatly alleviate the burdensome traditional method used to program a robot (greatly aids the end-user). We experiment with different modular configurations for the brain activity information, i.e., parallelized models and what we refer to as a global model for fusing the information. We explore various machine learning and pattern recognition techniques as well as existing feature selection methods. Our experimental results show that the subject can control the robot to a destination of interest using a machine—robot–interface. We attain accuracy in the order of 99.6% when it comes to the desired motion and 99.8% for the case of deducing the desired characteristic (color) of the targeted object. These results outperform any similar existing approaches that we have researched. Moreover, in comparison to those similar operational systems, we present a unique modular configuration for brain activity interpretation and object detection mechanism that yields an overall system that is highly computationally efficient. Although, in this work, we implemented and demoed our approach using a simple pick and place demo, our work presents the basic structure underlying a system that can be efficiently used to benefit people with restricted ability to function physically (tetraplegic patients), and allowing them to perform complex and robotics related duties in an industrial setting.

Doctor of Philosophy, The Ohio State University, 2024, Electrical and Computer Engineering

This dissertation addresses the integration of reinforcement learning (RL) with model-based methods to develop robust and efficient bipedal locomotion strategies for robots, highlighting the significance of these machines in navigating complex terrains and confined spaces. The quest for advanced bipedal robots is driven by their potential utility across various sectors, including terrain exploration, rescue missions, and assistive technologies. However, the inherent complexity of bipedal motion—marked by high-dimensional models, underactuation, and nonlinear dynamics—presents substantial hurdles in crafting effective motion synthesis techniques. The core of this research lies in devising innovative, learning-based frameworks that synergize the principles of control theory and the adaptability of RL. By encapsulating the hybrid nature of bipedal locomotion and leveraging reduced-order models, these frameworks aim to surmount the challenges of data efficiency and interpretability in controller design. The dissertation unfolds across a series of contributions that collectively enhance the understanding and capabilities of bipedal locomotion, eschewing a chapter-by-chapter exposition for a thematic discussion of key advances. A significant portion of the work is dedicated to developing RL-based frameworks that compartmentalize the bipedal locomotion challenge into trajectory planning and feedback regulation. Incorporating insights from the physics of walking, these frameworks reduce the complexity of policy inputs, leading to the creation of variable speed locomotion policies without relying on pre-established reference trajectories. These methodologies underscore the feasibility of implementing sophisticated locomotion strategies in real-world robots, as demonstrated on platforms like the Cassie and Digit robots. Further, the dissertation extends into the realm of data-driven techniques, proposing a novel integration of low-dimensional state representations wi (open full item for complete abstract)

Master of Science, The Ohio State University, 2024, Electrical and Computer Engineering

As manufacturing techniques such as topology optimization and additive manufacturing develop, components with increasing geometric complexity are becoming more common. Thus, it is necessary to develop automated non-destructive evaluation techniques that are adaptable to various surface geometries. This project seeks to leverage robotic simulation software to virtually plan and optimize eddy current inspections of various airplane components to detect flaws while eliminating false positives. The final deliverable will be a Robot Operating System (ROS) software package that generates an optimal tool path plan based on probe output for various scan resolutions.

Doctor of Philosophy (PhD), Ohio University, 2024, Industrial and Systems Engineering (Engineering and Technology)

With the onset of technology-driven solutions, the warehousing and logistics sectors are witnessing transformative advancements, one of which is the Robotic Compact Storage and Retrieval System (RCSRS). This research presents a comprehensive examination of RCSRS through three interrelated chapters. The first chapter provides an exhaustive literature review, presenting existing findings and gaps in different types of automated storage systems that have been studied, comparing their characteristics, similarities, and differences. The second chapter pioneers the study of robot travel time within RCSRS, introducing an innovative Mixed-Integer Non-Linear Programming (MINLP) model optimized using a Genetic Algorithm (GA) approach. This investigation primarily provides insights like the optimal placement of the Input/Output (I/O) point and the significance of digging time as a critical bottleneck, while also setting the stage for future research directions. Lastly, the third chapter studies the performance of three optimization algorithms in the RCSRS context: Genetic Algorithm (GA), Simulated Annealing (SA), and a novel Greedy Heuristic. This study aims to minimize robot bin moves, recognizing its direct impact on time and energy utilization. Remarkable findings such as the Greedy Heuristic's efficiency for moderate-sized order lists and the SA's aptness for larger order lists have been detailed. Together, these chapters offer an expansive view into RCSRS's potential and the strategies to harness it, contributing valuable insights and methodologies for the warehousing and logistics sectors. The research anticipates fostering advanced RCSRS designs, optimizing operations, and guiding future research in this transformative domain.

Doctor of Philosophy, Case Western Reserve University, 0, EMC - Mechanical Engineering

This dissertation introduces the nodal honeycomb lattice structure, inspired by conventional honeycomb and chiral structures, and designed for assembly compatibility, serving as a foundation for integrating additional system components. This structure facilitated the development of soft robots with shape-morphing skins and an untethered, soft-bodied robot. It addresses the gap in research on the practical applications of shape morphing in robotics by proposing a novel design approach that enhances the mobility and efficiency of soft robots through dynamic shape-changing capabilities. This allows robots to navigate through confined spaces more effectively than traditional designs. The work also details a metamaterial-based approach for developing an untethered, soft-bodied robot that overcomes the challenges of traditional fabrication methods through a semi-automated process involving 3D printing and discrete assembly. This process results in a customizable and scalable robot with multimodal and omnidirectional locomotion, addressing the need for fully integrated on-board systems for applications in diverse and unstructured environments. This dissertation demonstrates that the nodal honeycomb structure has the potential to serve as a foundational concept for application in various soft robotic designs.

Doctor of Philosophy, Case Western Reserve University, 2024, EECS - Electrical Engineering

The disturbances caused by the blood flow and beating heart motions are major concerns during catheter ablation procedures. Maintaining a stable and safe contact on the desired ablation point is essential for achieving effective lesions during the ablation procedure. This dissertation aims to provide a comprehensive solution to the interaction control problem of a novel MRI-actuated robotic intravascular cardiac catheter interacting with the beating heart surface under uncertainties, with the ultimate goal of facilitating an automated catheter ablation procedure. In this dissertation, the catheter ablation process is divided into two phases: a free landing phase and an ablation phase. First, the free-space forward dynamic modeling approaches of an MRI-actuated robotic catheter are investigated to model the robotic catheter in the free-landing phase. Two discrete-time dynamic models of the MRI-actuated robotic catheter are presented and evaluated. The first model presented is a full-body Cosserat-rod-based dynamic model based on the dynamic Cosserat-rod theory, where the dynamic Cosserat-rod PDEs and the Euler-Lagrange equation are respectively used to derive the dynamic equations of the flexible segments and rigid segments. The second model presented is a hybrid Cosserat-rod dynamic model, where the dynamic equation of the rigid segments is derived using the Euler-Lagrange equation and the shape of the flexible segments is derived using the static Cosserat-rod theory. The proposed dynamic models are compared and experimentally validated using the 3D positional trajectories collected from a catadioptric stereo tracking system. The analysis of the contact stability and contact safety of the MRI-actuated robotic catheter under beating heart motions and blow flow disturbances are presented for the ablation phase. A probabilistic formulation for modeling and evaluating the contact stability and the contact safety of the robotic intravascular cardiac cathete (open full item for complete abstract)

Master of Science (M.S.), University of Dayton, 2024, Aerospace Engineering

This research introduces an Origami-inspired dynamic spacecraft radiator, capable of adjusting heat rejection in response to orbital variations and extreme temperature fluctuations in lunar environments. The research centers around the square twist origami tessellation, an adaptable geometric structure with significant potential for revolutionizing radiative heat control in space. The investigative involves simulations of square twist origami tessellation panels using vector math and algebra. This study examines both a two-dimensional (2- D), infinitely thin tessellation, and a three-dimensional (3-D), rigidly-foldable tessellation, each characterized by an adjustable closure or actuation angle “φ”. Meticulously analyzed the heat loss characteristics of both the 2D and 3D radiators over a 180-degree range of actuation. Utilizing Monte Carlo Ray Tracing and the concept of “view factors”, the study quantifies radiative heat loss, exploring the interplay of emitted, interrupted, and escaped rays as the geometry adapts to various positions. This method allowed for an in-depth understanding of the changing radiative heat loss behavior as the tessellation actuates from fully closed to fully deployed. The findings reveal a significant divergence between the 2D and 3D square twist origami radiators. With an emissivity of 1, the 3D model demonstrated a slower decrease in the ratio of escaped to emitted rays (Ψ) as the closure/actuation angle increased, while the 2D model exhibited a more linear decline. This divergence underscores the superior radiative heat loss control capabilities of the 2D square twist origami geometry, offering a promising turndown ratio of 4.42, validating the model's efficiency and practicality for radiative heat loss control. Further exploration involved both non-rigidly and rigidly foldable radiator models. The non-rigidly foldable geometry, initially a theoretical concept, is realized through 3D modeling and physica (open full item for complete abstract)

Master of Sciences (Engineering), Case Western Reserve University, 2024, EECS - Electrical Engineering

Atrial fibrillation, a prevalent heart condition, poses significant health risks. Traditional treatment involves cardiac ablation catheters guided by x-ray fluoroscopy, which provides limited two-dimensional heart images and subjects patients to substantial radiation. Utilizing magnetic resonance imaging (MRI) in these procedures offers three-dimensional catheter visualization and eliminates radiation exposure. The MRI's magnetic field can be leveraged in order to control a robotic ablation catheter with small electromagnetic coils in the catheter tip. However, these coils may interact negatively with the MRI's radio-frequency transmitter, causing potential overheating. Prior research led to the development of a compact catheter prototype, primarily to demonstrate its fundamental operational principles. Nevertheless, this prototype's limited size renders it unsuitable for practical application within the human body. The aim of this thesis is to engineer a full-scale catheter, a task that presents considerable challenges due to the demanding conditions of the MRI environment and the occurrence of standing waves on uncoupled elongated wires. This prototype is designed to meet the kinematic workspace specifications identified in earlier studies, while also ensuring full compatibility with a human subject. The prototype maintains a low heat output and does not interfere with the MRI's functionality.

Doctor of Philosophy in Engineering, Cleveland State University, 2023, Washkewicz College of Engineering

Joint mechanics research relies on joint kinematics and kinetics measurements, represented from relative relationships of local coordinate systems (CS) belonging to bones of the joint. It's common to define these CSs from anatomical landmarks, which are sensitive to observer variability and often don't result in CS that best represent the functional motion of the joint. This work is presented in three articles addressing the following aims: 1) to develop a method to objectively define coordinate systems through optimization of unique passive movement paths, 2) to develop an alternative method to objectively define coordinates systems for joints with non-unique passive movement paths, and 3) to validate the methods in vitro. Article 1 introduces an objective method for calculating functional CS definitions for bones in joints that observe three-cylindrical-joint kinematic chain decomposition methods and applies the method on tibiofemoral joint specimens. This method is driven by low resistance joint motion during loading profiles and not from anatomical landmark selection. Significant improvements in CS reproducibility were observed with functional CS, compared to anatomical. Significant decreases in off-axis motion during passive flexion profiles were also observed with functional CS. Article 2 establishes benefits in using Functional CS in vitro with human cadaveric tibiofemoral joints and rat stifle joints. Functional CS, compared to anatomical, significantly 1) reduced variation in intra-knee kinematic response, 2) reduced kinematic cross-talk, 3) reduced variation in inter-knee kinematic response, and 4) improved force/torque control performance. Scalability was demonstrated, as benefits extended to rat stifle testing. Article 3 presents a method for establishing Functional-Aggregate vertebral CS in the spine. Functional motion is only used to optimize CS origins, because passive movement paths are non-unique in the spine. An aggregate of anatomical landmar (open full item for complete abstract)

Master of Science (M.S.), University of Dayton, 2023, Mechanical Engineering

This thesis presents the research that has been done in advancing topics in multi-robot coordinated path planning and singularity avoidance of mechanisms. For coordinated robots, an offline path planning solution has been developed that incorporates manufacturing constraints while taking into account the manipulator's kinematics and collision constraints. A loading dock optimization problem is first tackled due to it being a simpler system with one degree of freedom (DOF) while keeping the collaborative nature intact. Then the focus is shifted to spatial robots having 3 prismatic and/or revolute joints. This includes a discussion on the kinematics of the robots, the task allocation using a Tabu-Search Heuristic, and collision avoidance routines. The 3P robots have a one-to-one inverse kinematic solution with a unique configuration for any point within the workspace. This allows for a less computationally expensive optimization model. Finally, the path planning solution is applied to N overlapping 5R robots that have increased computational complexity due to one-to-many inverse kinematic solutions. As the number of links of the robot increases, the effort for combinatory collision checking routine explodes. Several simulations are presented to validate the proposed methodology. The research on singularity avoidance focuses on finding an actuating chain that can be attached to a mechanism to drive it in a singularity-free manner. For a single degree of freedom spatial mechanism, a reference frame attached to any of its links produces a continuous motion of this frame. Given the progression of this frame from the start through the end of the mechanism's motion, this research seeks to identify specific points relative to this moving reference frame. The points of interest are those that can be coupled with a second point determined in the fixed frame to act as the end joint locations for a spherical-prismatic-spherical (SPS) driving chain. If the selection of the poi (open full item for complete abstract)