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Education in computer science is a difficult endeavor, with learning a new programing language being a barrier to entry, especially for college freshman and high school students. Learning a first programming language requires understanding the syntax of the language, the algorithms to use, and any additional complexities the language carries. Often times this becomes a deterrent from learning computer science at all. Especially in high school, students may not want to spend a year or more simply learning the syntax of a programming language. In order to overcome these issues, as well as to mitigate the issues caused by Microsoft discontinuing their Visual Programming Language (VPL), we have decided to implement a new VPL, ASU-VPL, based on Microsoft's VPL. ASU-VPL provides an environment where users can focus on algorithms and worry less about syntactic issues. ASU-VPL was built with the concepts of Robot as a Service and workflow based development in mind. As such, ASU-VPL is designed with the intention of allowing web services to be added to the toolbox (e.g. WSDL and REST services). ASU-VPL has strong support for multithreaded operations, including event driven development, and is built with Microsoft VPL users in mind. It provides support for many different robots, including Lego's third generation robots, i.e. EV3, and any open platform robots. To demonstrate the capabilities of ASU-VPL, this paper details the creation of an Intel Edison based robot and the use of ASU-VPL for programming both the Intel based robot and an EV3 robot. This paper will also discuss differences between ASU-VPL and Microsoft VPL as well as differences between developing for the EV3 and for an open platform robot.
ContributorsDe Luca, Gennaro (Author) / Chen, Yinong (Thesis director) / Cheng, Calvin (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2015-12
Description
This thesis focused on grasping tasks with the goal of investigating, analyzing, and quantifying human catching trends by way of a mathematical model. The aim of this project was to study human trends in a dynamic grasping task (catching a rolling ball), relate those discovered trends to kinematic characteristics of the object, and use this relation to control a robot hand in real time. As an ultimate goal, it was hoped that this research will aide in furthering the bio-inspiration in robot control methods. To achieve the above goal, firstly a tactile sensing glove was developed. This instrument allowed for in depth study of human reactionary grasping movements when worn by subjects during experimentation. This sensing glove system recorded force data from the palm and motion data from four fingers. From these data sets, temporal trends were established relating to when subjects initiated grasping during each trial. Moreover, optical tracking was implemented to study the kinematics of the moving object during human experiments and also to close the loop during the control of the robot hand. Ultimately, a mathematical bio-inspired model was created. This was embodied in a two-term decreasing power function which related the temporal trend of wait time to the ball initial acceleration. The wait time is defined as the time between when the experimental conductor releases the ball and when the subject begins to initiate grasping by closing their fingers, over a distance of four feet. The initial acceleration is the first acceleration value of the object due to the force provided when the conductor throws the object. The distance over which the ball was thrown was incorporated into the model. This is discussed in depth within the thesis. Overall, the results presented here show promise for bio-inspired control schemes in the successful application of robotic devices. This control methodology will ideally be developed to move robotic prosthesis past discrete tasks and into more complicated activities.
ContributorsCard, Dillon (Co-author) / Mincieli, Jennifer (Co-author) / Artemiadis, Panagiotis (Thesis director) / Santos, Veronica (Committee member) / Middleton, James (Committee member) / Barrett, The Honors College (Contributor) / School of Sustainability (Contributor) / Mechanical and Aerospace Engineering Program (Contributor) / W. P. Carey School of Business (Contributor)
Created2014-05
Description
Robotic rehabilitation for upper limb post-stroke recovery is a developing technology. However, there are major issues in the implementation of this type of rehabilitation, issues which decrease efficacy. Two of the major solutions currently being explored to the upper limb post-stroke rehabilitation problem are the use of socially assistive rehabilitative robots, robots which directly interact with patients, and the use of exoskeleton-based systems of rehabilitation. While there is great promise in both of these techniques, they currently lack sufficient efficacy to objectively justify their costs. The overall efficacy to both of these techniques is about the same as conventional therapy, yet each has higher overhead costs that conventional therapy does. However there are associated long-term cost savings in each case, meaning that the actual current viability of either of these techniques is somewhat nebulous. In both cases, the problems which decrease technique viability are largely related to joint action, the interaction between robot and human in completing specific tasks, and issues in robot adaptability that make joint action difficult. As such, the largest part of current research into rehabilitative robotics aims to make robots behave in more "human-like" manners or to bypass the joint action problem entirely.
ContributorsRamakrishna, Vijay Kambhampati (Author) / Helms Tillery, Stephen (Thesis director) / Buneo, Christopher (Committee member) / Barrett, The Honors College (Contributor) / Economics Program in CLAS (Contributor) / W. P. Carey School of Business (Contributor) / School of Life Sciences (Contributor)
Created2015-05
Description
A common design of multi-agent robotic systems requires a centralized master node, which coordinates the actions of all the agents. The multi-agent system designed in this project enables coordination between the robots and reduces the dependence on a single node in the system. This design change reduces the complexity of the central node, and makes the system more adaptable to changes in its topology. The final goal of this project was to have a group of robots collaboratively claim positions in pre-defined formations, and navigate to the position using pose data transmitted by a localization server.
Planning coordination between robots in a multi-agent system requires each robot to know the position of the other robots. To address this, the localization server tracked visual fiducial markers attached to the robots and relayed their pose to every robot at a rate of 20Hz using the MQTT communication protocol. The robots used this data to inform a potential fields path planning algorithm and navigate to their target position.
This project was unable to address all of the challenges facing true distributed multi-agent coordination and needed to make concessions in order to meet deadlines. Further research would focus on shoring up these deficiencies and developing a more robust system.
Planning coordination between robots in a multi-agent system requires each robot to know the position of the other robots. To address this, the localization server tracked visual fiducial markers attached to the robots and relayed their pose to every robot at a rate of 20Hz using the MQTT communication protocol. The robots used this data to inform a potential fields path planning algorithm and navigate to their target position.
This project was unable to address all of the challenges facing true distributed multi-agent coordination and needed to make concessions in order to meet deadlines. Further research would focus on shoring up these deficiencies and developing a more robust system.
ContributorsThibeault, Quinn (Author) / Meuth, Ryan (Thesis director) / Chen, Yinong (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Classical planning is a field of Artificial Intelligence concerned with allowing autonomous agents to make reasonable decisions in complex environments. This work investigates
the application of deep learning and planning techniques, with the aim of constructing generalized plans capable of solving multiple problem instances. We construct a Deep Neural Network that, given an abstract problem state, predicts both (i) the best action to be taken from that state and (ii) the generalized “role” of the object being manipulated. The neural network was tested on two classical planning domains: the blocks world domain and the logistic domain. Results indicate that neural networks are capable of making such
predictions with high accuracy, indicating a promising new framework for approaching generalized planning problems.
the application of deep learning and planning techniques, with the aim of constructing generalized plans capable of solving multiple problem instances. We construct a Deep Neural Network that, given an abstract problem state, predicts both (i) the best action to be taken from that state and (ii) the generalized “role” of the object being manipulated. The neural network was tested on two classical planning domains: the blocks world domain and the logistic domain. Results indicate that neural networks are capable of making such
predictions with high accuracy, indicating a promising new framework for approaching generalized planning problems.
ContributorsNakhleh, Julia Blair (Author) / Srivastava, Siddharth (Thesis director) / Fainekos, Georgios (Committee member) / Computer Science and Engineering Program (Contributor) / School of International Letters and Cultures (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
In this update to the ESPBot, we have introduced new libraries for a small OLED display and a beeper. This functionality can be easily expanded to multiple beepers and displays, but requires more GPIO pins, or for the user to not use some of the infrared sensors or the ultrasonic sensor. We have also relocated some of the pins. The display can be updated to display 1 of 4 predefined shapes, or to display user-defined text. New shapes can be added by defining new methods within display.ino and calling the appropriate functions while parsing the JSON data in viple.ino. The beeper can be controlled by user-defined input to play any frequency for any amount of time. There is also a function added to play the happy birthday song. More songs can be added by defining new methods within beeper.ino and calling the appropriate functions while parsing the JSON data in viple.ino. More functionality can be added to allow the user to input a list of frequencies along with a list of time so the user can define their own songs or sequences on the fly.
ContributorsWelfert, Monica Michelle (Co-author) / Nguyen, Van (Co-author) / Chen, Yinong (Thesis director) / Nakamura, Mutsumi (Committee member) / Computer Science and Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-12
Description
For those interested in the field of robotics, there are not many options to get your hands on a physical robot without paying a steep price. This is why the folks at BCN3D Technologies decided to design a fully open-source 3D-printable robotic arm. Their goal was to reduce the barrier to entry for the field of robotics and make it exponentially more accessible for people around the world. For our honors thesis, we chose to take the design from BCN3D and attempt to build their robot, to see how accessible the design truly is. Although their designs were not perfect and we were forced to make some adjustments to the 3D files, overall the work put forth by the people at BCN3D was extremely useful in successfully building a robotic arm that is programmed with ease.
ContributorsCohn, Riley (Co-author) / Petty, Charles (Co-author) / Ben Amor, Hani (Thesis director) / Yong, Sze Zheng (Committee member) / Computer Science and Engineering Program (Contributor) / Mechanical and Aerospace Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12
Description
This study presents quantification of ankle stability as affected by environmental conditions in two degrees of freedom (DOF) with three distinct analysis techniques. Additionally, this study presents gender-specific trends for comparison. Intuitively, ankle stability decreased in less stable environments with a negative simulated stiffness. Female subjects generally suffered a greater loss of stability in moderately and highly unstable environments. Both gender groups exhibited greater stability in the sagittal plane than the frontal plane across the entire range of simulated stiffness's. Outcomes of this study are useful in the design of controllers for lower extremity physically-interactive robotics, understanding situations in which the ankle is likely to lose stability, and understanding the strengths and weaknesses of unique analysis techniques.
ContributorsHanzlick, Harrison Patrick (Author) / Lee, Hyunglae (Thesis director) / Artemiadis, Panagiotis (Committee member) / Mechanical and Aerospace Engineering Program (Contributor) / W. P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12
Description
The goal of this project is to use an open-source solution to implement a drone Cyber-Physical System that can fly autonomously and accurately. The proof-of-concept to analyze the drone's flight capabilities is to fly in a pattern corresponding to the outline of an image, a process that requires both stability and precision to accurately depict the image. In this project, we found that building a Cyber-Physical System is difficult because of the tedious and complex nature of designing and testing the hardware and software solutions of this system. Furthermore, we reflect on the difficulties that arose from using open-source hardware and software.
ContributorsDedinsky, Rachel (Co-author) / Lubbers, Harrison James (Co-author) / Shrivastava, Aviral (Thesis director) / Dougherty, Ryan (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
This thesis describes a multi-robot architecture which allows teams of robots to work with humans to complete tasks. The multi-agent architecture was built using Robot Operating System and Python. This architecture was designed modularly, allowing the use of different planners and robots. The system automatically replans when robots connect or disconnect. The system was demonstrated on two real robots, a Fetch and a PeopleBot, by conducting a surveillance task on the fifth floor of the Computer Science building at Arizona State University. The next part of the system includes extensions for teaming with humans. An Android application was created to serve as the interface between the system and human teammates. This application provides a way for the system to communicate with humans in the loop. In addition, it sends location information of the human teammates to the system so that goal recognition can be performed. This goal recognition allows the generation of human-aware plans. This capability was demonstrated in a mock search and rescue scenario using the Fetch to locate a missing teammate.
ContributorsSaba, Gabriel Christer (Author) / Kambhampati, Subbarao (Thesis director) / Doupé, Adam (Committee member) / Chakraborti, Tathagata (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05