Matching Items (6)

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Design and Fabrication of a Low-Cost Gripper for a Swarm Robotic Platform

Description

This thesis details the design and construction of a torque-controlled robotic gripper for use with the Pheeno swarm robotics platform. This project required expertise from several fields of study including: robotic design, programming, rapid prototyping, and control theory. An electronic

This thesis details the design and construction of a torque-controlled robotic gripper for use with the Pheeno swarm robotics platform. This project required expertise from several fields of study including: robotic design, programming, rapid prototyping, and control theory. An electronic Inertial Measurement Unit and a DC Motor were both used along with 3D printed plastic components and an electronic motor control board to develop a functional open-loop controlled gripper for use in collective transportation experiments. Code was developed that effectively acquired and filtered rate of rotation data alongside other code that allows for straightforward control of the DC motor through experimentally derived relationships between the voltage applied to the DC motor and the torque output of the DC motor. Additionally, several versions of the physical components are described through their development.

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Date Created
2019-05

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An Investigation of Morality in Driving Situations as a Basis for Determining Autonomous Vehicle Ethics

Description

As urban populations increase, so does the demand for innovative transportation solutions which reduce traffic congestion, reduce pollution, and reduce inequalities by providing mobility for all kinds of people. One emerging solution is self-driving vehicles, which have been coined as

As urban populations increase, so does the demand for innovative transportation solutions which reduce traffic congestion, reduce pollution, and reduce inequalities by providing mobility for all kinds of people. One emerging solution is self-driving vehicles, which have been coined as a safer driving method by reducing fatalities due to driving accidents. While completely automated vehicles are still in the testing and development phase, the United Nations predict their full debut by 2030 [1]. While many resources are focusing their time on creating the technology to execute decisions such as the controls, communications, and sensing, engineers often leave ethics as an afterthought. The truth is autonomous vehicles are imperfect systems that will still experience possible crash scenarios even if all systems are working perfectly. Because of this, ethical machine learning must be considered and implemented to avoid an ethical catastrophe which could delay or completely halt future autonomous vehicle development. This paper presents an experiment for determining a more complete view of human morality and how this translates into ideal driving behaviors.
This paper analyzes responses to deviated Trolley Problem scenarios [5] in a simulated driving environment and still images from MIT’s moral machine website [8] to better understand how humans respond to various crashes. Also included is participants driving habits and personal values, however the bulk of that analysis is not included here. The results of the simulation prove that for the most part in driving scenarios, people would rather sacrifice themselves over people outside of the vehicle. The moral machine scenarios prove that self-sacrifice changes as the trend to harm one’s own vehicle was not so strong when passengers were introduced. Further defending this idea is the importance placed on Family Security over any other value.
Suggestions for implementing ethics into autonomous vehicle crashes stem from the results of this experiment but are dependent on more research and greater sample sizes. Once enough data is collected and analyzed, a moral baseline for human’s moral domain may be agreed upon, quantified, and turned into hard rules governing how self-driving cars should act in different scenarios. With these hard rules as boundary conditions, artificial intelligence should provide training and incremental learning for scenarios which cannot be determined by the rules. Finally, the neural networks which make decisions in artificial intelligence must move from their current “black box” state to something more traceable. This will allow researchers to understand why an autonomous vehicle made a certain decision and allow tweaks as needed.

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Created

Date Created
2019-05

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Variable Damping Control of the Robotic Ankle Joint to Improve Trade-off between Agility and Stability

Description

This paper presents a variable damping controller that can be implemented into wearable and exoskeleton robots. The variable damping controller functions by providing different levels of robotic damping from negative to positive to the coupled human-robot system. The wearable ankle

This paper presents a variable damping controller that can be implemented into wearable and exoskeleton robots. The variable damping controller functions by providing different levels of robotic damping from negative to positive to the coupled human-robot system. The wearable ankle robot was used to test this control strategy in the different directions of motion. The range of damping applied was selected based on the known inherent damping of the human ankle, ensuring that the coupled system became positively damped, and therefore stable. Human experiments were performed to understand and quantify the effects of the variable damping controller on the human user. Within the study, the human subjects performed a target reaching exercise while the ankle robot provided the system with constant positive, constant negative, or variable damping. These three damping conditions could then be compared to analyze the performance of the system. The following performance measures were selected: maximum speed to quantify agility, maximum overshoot to quantify stability, and muscle activation to quantify effort required by the human user. Maximum speed was found to be statistically the same in the variable damping controller and the negative damping condition and to be increased from positive damping controller to variable damping condition by 57.9%, demonstrating the agility of the system. Maximum overshoot was found to significantly decrease overshoot from the negative damping condition to the variable damping controller by 39.6%, demonstrating an improvement in system stability with the variable damping controller. Muscle activation results showed that the variable damping controller required less effort than the positive damping condition, evidenced by the decreased muscle activation of 23.8%. Overall, the study demonstrated that a variable damping controller can balance the trade-off between agility and stability in human-robot interactions and therefore has many practical implications.

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Date Created
2019-12

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Analysis of Local Minima arising from Potential-Based Controllers for Multi-Robot Transport with Convex Obstacle Avoidance

Description

This thesis presents a process by which a controller used for collective transport tasks is qualitatively studied and probed for presence of undesirable equilibrium states that could entrap the system and prevent it from converging to a target state. Fields

This thesis presents a process by which a controller used for collective transport tasks is qualitatively studied and probed for presence of undesirable equilibrium states that could entrap the system and prevent it from converging to a target state. Fields of study relevant to this project include dynamic system modeling, modern control theory, script-based system simulation, and autonomous systems design. Simulation and computational software MATLAB and Simulink® were used in this thesis.
To achieve this goal, a model of a swarm performing a collective transport task in a bounded domain featuring convex obstacles was simulated in MATLAB/ Simulink®. The closed-loop dynamic equations of this model were linearized about an equilibrium state with angular acceleration and linear acceleration set to zero. The simulation was run over 30 times to confirm system ability to successfully transport the payload to a goal point without colliding with obstacles and determine ideal operating conditions by testing various orientations of objects in the bounded domain. An additional purely MATLAB simulation was run to identify local minima of the Hessian of the navigation-like potential function. By calculating this Hessian periodically throughout the system’s progress and determining the signs of its eigenvalues, a system could check whether it is trapped in a local minimum, and potentially dislodge itself through implementation of a stochastic term in the robot controllers. The eigenvalues of the Hessian calculated in this research suggested the model local minima were degenerate, indicating an error in the mathematical model for this system, which likely incurred during linearization of this highly nonlinear system.

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Created

Date Created
2020-12

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Adsorption Cooling System Test Bed Design

Description

Current applications of the traditional vapor-compression refrigeration system are not feasible. Space cooling and refrigeration systems that employ vapor-compression refrigeration cycles utilize harmful refrigerants, produce large amounts of carbon dioxide, and have high energy consumption. Adsorption cooling technology is seen

Current applications of the traditional vapor-compression refrigeration system are not feasible. Space cooling and refrigeration systems that employ vapor-compression refrigeration cycles utilize harmful refrigerants, produce large amounts of carbon dioxide, and have high energy consumption. Adsorption cooling technology is seen as a possible alternative to traditional vapor-compression refrigeration systems. The low-grade heat requirement and eco-friendly adsorbent and refrigerant materials make adsorption cooling an attractive technology. Adsorption cooling technology employs the adsorption principle—the phenomenon in which an adsorbate fluid adheres to the surfaces and micropores of an adsorbent solid. The purpose of this study was to explore the adsorption cooling process through the use of a prototype adsorption test bed design. A basic intermittent adsorption cooling cycle was utilized for the test bed design. Several requirements for the design include low-cost, simple fabrication, and capable of holding a vacuum. In this study, an experiment was carried out to analyze the desorption process, in which the original weight of adsorbed water was compared to the weight of the desorbed water. The system pressure was decreased to sub-atmospheric absolute pressure of 16.67 kPa in order to increase the desorption rate and drive the desorption process. A hot water pump provided 81.6 °C hot water to heat the adsorption bed. The desorption process lasted for a duration of 162 minutes. The experiment resulted in 3.60 g (16.04%) of the initial adsorbed water being desorbed during the desorption process. The study demonstrates the potential of adsorption cooling. This paper outlines the design, fabrication, and analysis of a prototype adsorption cooling test bed.

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Created

Date Created
2019-05

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Fuel Cell Integrated Gas Turbine Hybrid System Under Various Conditions

Description

A novel concept for integration of flame-assisted fuel cells (FFC) with a gas turbine is analyzed in this paper. Six different fuels (CH4, C3H8, JP-4, JP-5, JP-10(L), and H2) are investigated for the analytical model of the FFC integrated gas

A novel concept for integration of flame-assisted fuel cells (FFC) with a gas turbine is analyzed in this paper. Six different fuels (CH4, C3H8, JP-4, JP-5, JP-10(L), and H2) are investigated for the analytical model of the FFC integrated gas turbine hybrid system. As equivalence ratio increases, the efficiency of the hybrid system increases initially then decreases because the decreasing flow rate of air begins to outweigh the increasing hydrogen concentration. This occurs at an equivalence ratio of 2 for CH4. The thermodynamic cycle is analyzed using a temperature entropy diagram and a pressure volume diagram. These thermodynamic diagrams show as equivalence ratio increases, the power generated by the turbine in the hybrid setup decreases. Thermodynamic analysis was performed to verify that energy is conserved and the total chemical energy going into the system was equal to the heat rejected by the system plus the power generated by the system. Of the six fuels, the hybrid system performs best with H2 as the fuel. The electrical efficiency with H2 is predicted to be 27%, CH4 is 24%, C3H8 is 22%, JP-4 is 21%, JP-5 is 20%, and JP-10(L) is 20%. When H2 fuel is used, the overall integrated system is predicted to be 24.5% more efficient than the standard gas turbine system. The integrated system is predicted to be 23.0% more efficient with CH4, 21.9% more efficient with C3H8, 22.7% more efficient with JP-4, 21.3% more efficient with JP-5, and 20.8% more efficient with JP-10(L). The sensitivity of the model is investigated using various fuel utilizations. When CH4 fuel is used, the integrated system is predicted to be 22.7% more efficient with a fuel utilization efficiency of 90% compared to that of 30%.

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Date Created
2021-05