Matching Items (65)

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Human Perception of Swarm Behavior

Description

This thesis focused on understanding how humans visually perceive swarm behavior through the use of swarm simulations and gaze tracking. The goal of this project was to determine visual patterns

This thesis focused on understanding how humans visually perceive swarm behavior through the use of swarm simulations and gaze tracking. The goal of this project was to determine visual patterns subjects display while observing and supervising a swarm as well as determine what swarm characteristics affect these patterns. As an ultimate goal, it was hoped that this research will contribute to optimizing human-swarm interaction for the design of human supervisory controllers for swarms. To achieve the stated goals, two investigations were conducted. First, subjects gaze was tracked while observing a simulated swarm as it moved across the screen. This swarm changed in size, disturbance level in the position of the agents, speed, and path curvature. Second, subjects were asked to play a supervisory role as they watched a swarm move across the screen toward targets. The subjects determined whether a collision would occur and with which target while their responses as well as their gaze was tracked. In the case of an observatory role, a model of human gaze was created. This was embodied in a second order model similar to that of a spring-mass-damper system. This model was similar across subjects and stable. In the case of a supervisory role, inherent weaknesses in human perception were found, such as the inability to predict future position of curved paths. These findings are discussed in depth within the thesis. Overall, the results presented suggest that understanding human perception of swarms offers a new approach to the problem of swarm control. The ability to adapt controls to the strengths and weaknesses could lead to great strides in the reduction of operators in the control of one UAV, resulting in a move towards one man operation of a swarm.

Contributors

Created

Date Created
  • 2015-05

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Statistically Based Registration in Sensor Networks

Description

In recent years, networked systems have become prevalent in communications, computing, sensing, and many other areas. In a network composed of spatially distributed agents, network-wide synchronization of information about the

In recent years, networked systems have become prevalent in communications, computing, sensing, and many other areas. In a network composed of spatially distributed agents, network-wide synchronization of information about the physical environment and the network configuration must be maintained using measurements collected locally by the agents. Registration is a process for connecting the coordinate frames of multiple sets of data. This poses numerous challenges, particularly due to availability of direct communication only between neighboring agents in the network. These are exacerbated by uncertainty in the measurements and also by imperfect communication links. This research explored statistically based registration in a sensor network. The approach developed exploits measurements of offsets formed as differences of state values between pairs of agents that share a link in the network graph. It takes into account that the true offsets around any closed cycle in the network graph must sum to zero.

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Created

Date Created
  • 2014-05

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An Adaptive Boundary Coverage Control Strategy for Swarm Robotic Systems

Description

This thesis presents an approach to design and implementation of an adaptive boundary coverage control strategy for a swarm robotic system. Several fields of study are relevant to this project,

This thesis presents an approach to design and implementation of an adaptive boundary coverage control strategy for a swarm robotic system. Several fields of study are relevant to this project, including; dynamic modeling, control theory, programming, and robotic design. Tools and techniques from these fields were used to design and implement a model simulation and an experimental testbed. To achieve this goal, a simulation of the boundary coverage control strategy was first developed. This simulated model allowed for concept verification for different robot groups and boundary designs. The simulation consisted of a single, constantly expanding circular boundary with a modeled swarm of robots that autonomously allocate themselves around the boundary. Ultimately, this simulation was implemented in an experimental testbed consisting of mobile robots and a moving boundary wall to exhibit the behaviors of the simulated robots. The conclusions from this experiment are hoped to help make further advancements to swarm robotic technology. The results presented show promise for future progress in adaptive control strategies for robotic swarms.

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Created

Date Created
  • 2017-05

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Development of Graphical User Interfaces and Algorithms for Controlling a Robotic Swarm

Description

The aim of this project was to develop user-friendly methods for programming and controlling a new type of small robot platform, called Pheeno, both individually and as part of a

The aim of this project was to develop user-friendly methods for programming and controlling a new type of small robot platform, called Pheeno, both individually and as part of a group. Two literature reviews are presented to justify the need for these robots and to discuss what other platforms have been developed for similar applications. In order to accomplish control of multiple robots work was done on controlling a single robot first. The response of a gripper arm attachment for the robot was smoothed, graphical user interfaces were developed, and commands were sent to a single robot using a video game controller. For command of multiple robots a class was developed in Python to make it simpler to send commands and keep track of different characteristics of each individual robot. A simple script was also created as a proof of concept to show how threading could be used to send different commands simultaneously to multiple robots in order to test algorithms on a group of robots. The class and two other scripts necessary for implementing the class are also presented to make it possible for future use of the given work.

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Created

Date Created
  • 2016-05

A Concept for Using Superformula and Information Theory to Identify and Prioritize Interesting Objects in Autonomous Exploration

Description

In order to refine autonomous exploratory movement planning schemes, an approach must be developed that accounts for valuable information other than that gained from map filling. To this end, the

In order to refine autonomous exploratory movement planning schemes, an approach must be developed that accounts for valuable information other than that gained from map filling. To this end, the goal of this thesis is divided into two parts. The first is to develop a technique for categorizing objects detected by an autonomous exploratory robot and assigning them a score based on their interest value. The second is an attempt to develop a method of integrating this technique into a navigation algorithm in order to refine the movements of a robot or robots to maximize the efficiency of information gain. The intention of both of these components is to provide a method of refining the navigation scheme applied to autonomous exploring robots and maximize the amount of information they can gather in deployments where they face significant resource or functionality constraints. To this end this project is divided into two main sections: a shape-matching technique and a simulation in in which to implement this technique. The first section was accomplished by combining concepts from information theory, principal component analysis, and the eigenfaces algorithm to create an effective matching technique. The second was created with inspiration from existing navigation algorithms. Once these components were determined to be functional, a testing regime was applied to determine their capabilities. The testing regime was also divided into two parts. The tests applied to the matching technique were first to demonstrate that it functions under ideal conditions. After testing was conducted under ideal conditions, the technique was tested under non-ideal conditions. Additional tests were run to determine how the system responded to changes in the coefficients and equations that govern its operation. Similarly, the simulation component was initially tested under normal conditions to determine the base effectiveness of the approach. After these tests were conducted, alternative conditions were tested to evaluate the effects of modifying the implementation technique. The results of these tests indicated a few things. The first series of tests confirmed that the matching technique functions as expected under ideal conditions. The second series of tests determined that the matching element is effective for a reasonable range of variations and non-ideal conditions. The third series of tests showed that changing the functional coefficients of the matching technique can help tune the technique to different conditions. The fourth series of tests demonstrated that the basic concept of the implementation technique makes sense. The final series of tests demonstrated that modifying the implementation method is at least somewhat effective and that modifications to it can be used to specifically tailor the implementation to a method. Overall the results indicate that the stated goals of the project were accomplished successfully.

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Agent

Created

Date Created
  • 2016-12

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Design and Simulation of Controllers for Multi-Robot Transport over Inclines

Description

The goal of this thesis is designing controllers for swarm robots transport a payload over inclines. Several fields of study are related to this study, including control theory, dynamic modeling

The goal of this thesis is designing controllers for swarm robots transport a payload over inclines. Several fields of study are related to this study, including control theory, dynamic modeling and programming. MATLAB, a tool of design controller and simulation, is used in this thesis.

To achieve this goal, a model of swarm robots transportation should be designed, which is cruise control for this scenario. Secondly, based on free body diagram, force equilibrium equation can be deduced. Then, the function of plant can be deduced based on cruise control and force equilibrium equations. Thirdly, list potential controllers, which may implement desired controls of swarm robots, and test their performance. Modify value of gains and do simulations of these controller. After analyzing results of simulation, the best controller can be selected.

In the last section, there is conclusion of entire thesis project and pointing out future work. The section of future work will mention potential difficulties of building entire control system, which allow swarm robots transport over inclines in real environment.

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Agent

Created

Date Created
  • 2019-05

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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:

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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Created

Date Created
  • 2019-05

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Attitudes Towards Autonomous Vehicles (AVs): Insights Gained through Surveys and Proposed Experiments on a Small-Scale Traffic Testbed

Description

In the next decade or so, there will be a shift in the industry of transportation across the world. Already today we have autonomous vehicles (AVs) tested in the Greater

In the next decade or so, there will be a shift in the industry of transportation across the world. Already today we have autonomous vehicles (AVs) tested in the Greater Phoenix area showing that the technology has improved to a level available to the public eye. Although this technology is not yet released commercially (for the most part), it is being used and will continue to be used to develop a safer future. With a high incidence of human error causing accidents, many expect that autonomous vehicles will be safer than human drivers. They do still require driver attention and sometimes intervention to ensure safety, but for the most part are much safer. In just the United States alone, there were 40,000 deaths due to car accidents last year [1]. If traffic fatalities were considered a disease, this would be an epidemic. The technology behind autonomous vehicles will allow for a much safer environment and increased mobility and independence for people who cannot drive and struggle with public transport. There are many opportunities for autonomous vehicles in the transportation industry. Companies can save a lot more money on shipping by cutting the costs of human drivers and trucks on the road, even allowing for simpler drop shipments should the necessary AI be developed.Research is even being done by several labs at Arizona State University. For example, Dr. Spring Berman’s Autonomous Collective Systems Lab has been collaborating with Dr. Nancy Cooke of Human Systems Engineering to develop a traffic testbed, CHARTopolis, to study the risks of driver-AV interactions and the psychological effects of AVs on human drivers on a small scale. This testbed will be used by researchers from their labs and others to develop testing on reaction, trust, and user experience with AVs in a safe environment that simulates conditions similar to those experienced by full-size AVs. Using a new type of small robot that emulates an AV, developed in Dr. Berman’s lab, participants will be able to remotely drive around a model city environment and interact with other AV-like robots using the cameras and LiDAR sensors on the remotely driven robot to guide them.
Although these commercial and research systems are still in testing, it is important to understand how AVs are being marketed to the general public and how they are perceived, so that one day they may be effectively adopted into everyday life. People do not want to see a car they do not trust on the same roads as them, so the questions are: why don’t people trust them, and how can companies and researchers improve the trustworthiness of the vehicles?

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Agent

Created

Date Created
  • 2019-05

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Image Processing for an Autonomous Throwing Arm and Smart Catching System

Description

In this paper, we propose an autonomous throwing and catching system to be developed as a preliminary step towards the refinement of a robotic arm capable of improving strength and

In this paper, we propose an autonomous throwing and catching system to be developed as a preliminary step towards the refinement of a robotic arm capable of improving strength and motor function in the limb. This will be accomplished by first autonomizing simpler movements, such as throwing a ball. In this system, an autonomous thrower will detect a desired target through the use of image processing. The launch angle and direction necessary to hit the target will then be calculated, followed by the launching of the ball. The smart catcher will then detect the ball as it is in the air, calculate its expected landing location based on its initial trajectory, and adjust its position so that the ball lands in the center of the target. The thrower will then proceed to compare the actual landing position with the position where it expected the ball to land, and adjust its calculations accordingly for the next throw. By utilizing this method of feedback, the throwing arm will be able to automatically correct itself. This means that the thrower will ideally be able to hit the target exactly in the center within a few throws, regardless of any additional uncertainty in the system. This project will focus of the controller and image processing components necessary for the autonomous throwing arm to be able to detect the position of the target at which it will be aiming, and for the smart catcher to be able to detect the position of the projectile and estimate its final landing position by tracking its current trajectory.

Contributors

Agent

Created

Date Created
  • 2018-05

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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

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.

Contributors

Created

Date Created
  • 2019-05