21 research outputs found

    Decentralized Multi-Floor Exploration by a Swarm of Miniature Robots Teaming with Wall-Climbing Units

    Full text link
    In this paper, we consider the problem of collectively exploring unknown and dynamic environments with a decentralized heterogeneous multi-robot system consisting of multiple units of two variants of a miniature robot. The first variant-a wheeled ground unit-is at the core of a swarm of floor-mapping robots exhibiting scalability, robustness and flexibility. These properties are systematically tested and quantitatively evaluated in unstructured and dynamic environments, in the absence of any supporting infrastructure. The results of repeated sets of experiments show a consistent performance for all three features, as well as the possibility to inject units into the system while it is operating. Several units of the second variant-a wheg-based wall-climbing unit-are used to support the swarm of mapping robots when simultaneously exploring multiple floors by expanding the distributed communication channel necessary for the coordinated behavior among platforms. Although the occupancy-grid maps obtained can be large, they are fully distributed. Not a single robotic unit possesses the overall map, which is not required by our cooperative path-planning strategy.Comment: Accepted for publication in IEEE-MRS 2019, Rutgers University, New Brunswick (NJ), US

    Designettes: An Approach to Multidisciplinary Engineering Design Education

    Get PDF
    Design and other fundamental topics in engineering are often isolated to dedicated courses. An opportunity exists to foster a culture of engineering design and multidisciplinary problem solving throughout the curriculum. Designettes, charettelike design challenges, are rapid and creative learning tools that enable educators to integrate design learning in a single class, across courses, across terms, and across disciplines. When two or more courses join together in a designette, a multidisciplinary learning activity occurs; multiple subjects are integrated and applied to open-ended problems and grand challenges. This practice helps foster a culture of design, and enables the introduction of multidisciplinary design challenges. Studies at the Singapore University of Technology and Design (SUTD) demonstrate learning of engineering subject matter in a bio-inspired robotics designette (MechAnimal), an interactive musical circuit designette, and an automated milk delivery (AutoMilk) designette. Each challenge combines problem clarification, concept generation, and prototyping with subject content such as circuits, biology, thermodynamics, differential equations, or software with controls. From pre- and postsurveys of students, designettes are found to increase students' understanding of engineering concepts. From 321 third-semester students, designettes were found to increase students' perceptions of their ability to solve multidisciplinary problems

    Development of magnetic field-based multisensor system for multi-DOF actuators

    Get PDF
    Growing needs for precise manipulation in medical surgery, manufacturing automation and structural health monitoring have motivated development of high accuracy, bandwidth and cost-effective sensing systems. Among these is a class of multi-axis electromagnetic devices where embedded magnetic fields can be capitalized for compact position estimation eliminating unwanted friction, stiction and inertia arising from dedicated and separate sensing mechanisms. Using fields for position measurements, however, is a challenging 'inverse problem' since they are often modeled in the 'forward' sense and their inverse solutions are often highly non-linear and non-unique. A general method to design a multisensor system that capitalizes on the existing magnetic field in permanent magnet (PM) actuators is presented. This method takes advantage of the structural field symmetry and meticulous placement of sensors to discretize the motion range of a PM-based device into smaller magnetic field segments, thereby reducing the required characterization domain. Within these localized segments, unique field-position correspondence is induced using field measurements from a network of multiple-axis sensors. A direct mapping approach utilizing trained artificial neural networks to attain multi-DOF positional information from distributed field measurements is employed as an alternative to existing computationally intensive model based methods which are unsuitable for real-time control implementation. Validation and evaluation of this technique are performed through field simulations and experimental investigation on an electromagnetic spherical actuator. An inclinometer was used as a performance comparison and experimental results have corroborated the superior tracking ability of the field-based sensing system. While the immediate application is field-based orientation determination of an electromagnetic actuator, it is expected that the design method can be extended to develop other sensing systems that harnesses other scalar, vector and tensor fields.PhDCommittee Chair: Lee, Kok-Meng; Committee Member: Sadegh, Nader; Committee Member: Singhose, William; Committee Member: Wang, Yang; Committee Member: Zhang, Fumi

    High Accuracy Passive Magnetic Field-Based Localization for Feedback Control Using Principal Component Analysis

    No full text
    In this paper, a novel magnetic field-based sensing system employing statistically optimized concurrent multiple sensor outputs for precise field-position association and localization is presented. This method capitalizes on the independence between simultaneous spatial field measurements at multiple locations to induce unique correspondences between field and position. This single-source-multi-sensor configuration is able to achieve accurate and precise localization and tracking of translational motion without contact over large travel distances for feedback control. Principal component analysis (PCA) is used as a pseudo-linear filter to optimally reduce the dimensions of the multi-sensor output space for computationally efficient field-position mapping with artificial neural networks (ANNs). Numerical simulations are employed to investigate the effects of geometric parameters and Gaussian noise corruption on PCA assisted ANN mapping performance. Using a 9-sensor network, the sensing accuracy and closed-loop tracking performance of the proposed optimal field-based sensing system is experimentally evaluated on a linear actuator with a significantly more expensive optical encoder as a comparison

    Organized Sensor Network Design for Active Feedback Control

    No full text
    Abstract-Active continuous control of systems using physical sensors are hindered by presence of corrupting noise in discretized measurements which degrades performance. This paper presents a systematic development of organized sensor networks that fuses the dynamic implementation of parallel and sequential network architectures with conventional multisensor filtering techniques to improve performance through collaborative network enhancement of noise suppression and sampling rate. The classical control of an inverted pendulum using vision sensors is presented as an illustrative example. Simulation results suggest that an organized sensor network with dynamic throttling outperforms a static network while minimizing overall sensor utilization

    Spherical Indoor Coandă Effect Drone (SpICED): A Spherical Blimp sUAS for Safe Indoor Use

    No full text
    Even as human–robot interactions become increasingly common, conventional small Unmanned Aircraft Systems (sUAS), typically multicopters, can still be unsafe for deployment in an indoor environment in close proximity to humans without significant safety precautions. This is due to their fast-spinning propellers, and lack of a fail-safe mechanism in the event of a loss of power. A blimp, a non-rigid airship filled with lighter-than-air gases is inherently safer as it ’floats’ in the air and is generally incapable of high-speed motion. The Spherical Indoor Coandă Effect Drone (SpICED), is a novel, safe spherical blimp design propelled by closed impellers utilizing the Coandă effect. Unlike a multicopter or conventional propeller blimp, the closed impellers reduce safety risks to the surrounding people and objects, allowing for SpICED to be operated in close proximity with humans and opening up the possibility of novel human–drone interactions. The design implements multiple closed-impeller rotors as propulsion units to accelerate airflow along the the surface of the spherical blimp and produce thrust by utilising the Coandă effect. A cube configuration with eight uni-directional propulsion units is presented, together with the closed-loop Proportional–Integral–Derivative (PID) controllers, and custom control mixing algorithm for position and attitude control in all three axes. A physical prototype of the propulsion unit and blimp sUAS was constructed to experimentally validate the dynamic behavior and controls in a motion-captured environment, with the experimental results compared to the side-tetra configuration with four bi-directional propulsion units as presented in our previously published conference paper. An up to 40% reduction in trajectory control error was observed in the new cube configuration, which is also capable of motion control in all six Degrees of Freedom (DoF) with additional pitch and roll control when compared to the side-tetra configuration

    Spherical Indoor Coandă Effect Drone (SpICED): A Spherical Blimp sUAS for Safe Indoor Use

    No full text
    Even as human–robot interactions become increasingly common, conventional small Unmanned Aircraft Systems (sUAS), typically multicopters, can still be unsafe for deployment in an indoor environment in close proximity to humans without significant safety precautions. This is due to their fast-spinning propellers, and lack of a fail-safe mechanism in the event of a loss of power. A blimp, a non-rigid airship filled with lighter-than-air gases is inherently safer as it ’floats’ in the air and is generally incapable of high-speed motion. The Spherical Indoor Coandă Effect Drone (SpICED), is a novel, safe spherical blimp design propelled by closed impellers utilizing the Coandă effect. Unlike a multicopter or conventional propeller blimp, the closed impellers reduce safety risks to the surrounding people and objects, allowing for SpICED to be operated in close proximity with humans and opening up the possibility of novel human–drone interactions. The design implements multiple closed-impeller rotors as propulsion units to accelerate airflow along the the surface of the spherical blimp and produce thrust by utilising the Coandă effect. A cube configuration with eight uni-directional propulsion units is presented, together with the closed-loop Proportional–Integral–Derivative (PID) controllers, and custom control mixing algorithm for position and attitude control in all three axes. A physical prototype of the propulsion unit and blimp sUAS was constructed to experimentally validate the dynamic behavior and controls in a motion-captured environment, with the experimental results compared to the side-tetra configuration with four bi-directional propulsion units as presented in our previously published conference paper. An up to 40% reduction in trajectory control error was observed in the new cube configuration, which is also capable of motion control in all six Degrees of Freedom (DoF) with additional pitch and roll control when compared to the side-tetra configuration

    Future-proofing students in higher education with unmanned aerial vehicles technology: A knowledge management case study

    Get PDF
    In this paper we report experiences in implementing a new course ‘Understanding Drone & Robotics Technology – History, Usage, Ethics & Legal Issues’ at the Singapore Management University framed as a strategic knowledge management (KM) initiative in an institution of higher learning aimed at capturing, sharing and creating new knowledge about disruptive technologies such as unmanned aerial vehicles. We posit the new course as a knowledge innovation initiative (similar to a KM-enabled business case in a corporate setting) in support of the university’s mission and vision so as to deliver new value to students and to stay ahead of the latest technological developments. In line with a ‘normal’ KM initiative, we examine how the new learning and teaching initiative was conceived, pushed forward and eventually launched, creating a new multi-disciplinary learning experience for students, instructors and other stakeholders. We explain the knowledge strategy of the course and use I. Nonaka’s SECI framework to shed light on selected aspects of the pedagogical approach towards achieving the desired learning outcomes. Overall, the paper intends to make a case for more collaborative knowledge leadership as a strategic enabler of multi-disciplinary knowledge innovation in a rapidly changing higher education landscape
    corecore