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Articles 1 - 6 of 6
Full-Text Articles in Engineering
Deep Reinforcement Learning Of Variable Impedance Control For Object-Picking Tasks, Akshit Lunia
Deep Reinforcement Learning Of Variable Impedance Control For Object-Picking Tasks, Akshit Lunia
All Theses
The increasing deployment of robots in industries with varying tasks has accelerated the development of various control frameworks, enabling robots to replace humans in repetitive, exhaustive, and hazardous jobs. One critical aspect is the robots' interaction with their environment, particularly in unknown object-picking tasks, which involve intricate object weight estimations and calculations when lifting objects. In this study, a unique control framework is proposed to modulate the force exerted by a manipulator for lifting an unknown object, eliminating the need for feedback from a force/torque sensor. The framework utilizes a variable impedance controller to generate the required force, and an …
Improving Hexapod Platform Pose Accuracy - A Photogrammetry-Based Approach, Sourabh Karmakar
Improving Hexapod Platform Pose Accuracy - A Photogrammetry-Based Approach, Sourabh Karmakar
All Dissertations
The aim of this research is to make a newly constructed Stewart-Gough Platform-based test frame Tiger 66.1 operational by developing control software and estimating the error in its pose accuracy. The accuracy of the platform is affected by one source or multiple sources. The typical error sources are kinematic and structural, some of them originate from manufacturing imperfections, assembly deviations, elastic deformations, thermal deformations, and joint clearances which change the expected kinematic behavior of the manipulator. Also, some non-mechanical errors like transmission error, sensor accuracy, algorithm error, and truncation error in calculation contribute significantly in some cases. Using pose deviations …
Damage Detection With An Integrated Smart Composite Using A Magnetostriction-Based Nondestructive Evaluation Method: Integrating Machine Learning For Prediction, Christopher Nelon
Damage Detection With An Integrated Smart Composite Using A Magnetostriction-Based Nondestructive Evaluation Method: Integrating Machine Learning For Prediction, Christopher Nelon
All Dissertations
The development of composite materials for structural components necessitates methods for evaluating and characterizing their damage states after encountering loading conditions. Laminates fabricated from carbon fiber reinforced polymers (CFRPs) are lightweight alternatives to metallic plates; thus, their usage has increased in performance industries such as aerospace and automotive. Additive manufacturing (AM) has experienced a similar growth as composite material inclusion because of its advantages over traditional manufacturing methods. Fabrication with composite laminates and additive manufacturing, specifically fused filament fabrication (fused deposition modeling), requires material to be placed layer-by-layer. If adjacent plies/layers lose adhesion during fabrication or operational usage, the strength …
Laser Stabilization Through Optical Turbulence, Liam Vanderschaaf
Laser Stabilization Through Optical Turbulence, Liam Vanderschaaf
All Theses
Laser jitter presents a significant issue in the fields of laser communication and sensing. There are two main categories of positional noise in regards to the instantaneous centroid of a laser propagating over long distances: jitter resulting from optical turbulence and jitter resulting from mechanical vibrations. Optical turbulence was generated using Clemson University’s Variable Turbulence Generator (VTG). The VTG is capable of creating a desired level of optical turbulence that is comparable to atmospheric conditions with fried parameters greater than 0.3 cm. A gaussian laser was transmitted through the VTG and a system of Fast Steering Mirrors and Position Sensing …
An Application Of Optimized Bistable Laminates As A Low Velocity, Low Impact Mechanical Deterrent, Graham Lancaster
An Application Of Optimized Bistable Laminates As A Low Velocity, Low Impact Mechanical Deterrent, Graham Lancaster
All Theses
This research considers the problem of using bistable laminates as a mechanical deterrent to the impending impact of a particle. The structure will be controlled through an algorithm that will utilize piezoelectric devices to activate them in unison with the bistable laminate to successfully deter. A novel experimental setup will be constructed to ensure that the bistable laminate stays fixed when acting as a mechanical deterrent. Piezoelectricity is the main driving force of the bistable laminate to morph and this study will use a Macro Fiber Composite (MFC) actuator that contains piezoelectric ceramic rods in a patch to transfer electrical …
Soft Robotic Arms For Fall Mitigation: Design, Control And Evaluation, Param Malhotra
Soft Robotic Arms For Fall Mitigation: Design, Control And Evaluation, Param Malhotra
All Theses
Most fall mitigation devices present a heavy system that avoid injuries to the user by preventing the impact of a fall. They are dependent on the user capability or on the probability that the user falls in the assumed manner the system was designed for. Often that is not the case, hence this project initiates a novel concept of using soft robotic arms to prevent falls from happening in the first place itself and save the user from any injuries. This thesis describes the prototype and development of a soft continuum robotic backpack system. The system can validate its use …