Matching Items (4)
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- All Subjects: Autonomous Vehicle
- Creators: Asner, Greg
- Creators: Berman, Spring
Description
As robots become mechanically more capable, they are going to be more and more integrated into our daily lives. Over time, human’s expectation of what the robot capabilities are is getting higher. Therefore, it can be conjectured that often robots will not act as human commanders intended them to do. That is, the users of the robots may have a different point of view from the one the robots do.
The first part of this dissertation covers methods that resolve some instances of this mismatch when the mission requirements are expressed in Linear Temporal Logic (LTL) for handling coverage, sequencing, conditions and avoidance. That is, the following general questions are addressed:
* What cause of the given mission is unrealizable?
* Is there any other feasible mission that is close to the given one?
In order to answer these questions, the LTL Revision Problem is applied and it is formulated as a graph search problem. It is shown that in general the problem is NP-Complete. Hence, it is proved that the heuristic algorihtm has 2-approximation bound in some cases. This problem, then, is extended to two different versions: one is for the weighted transition system and another is for the specification under quantitative preference. Next, a follow up question is addressed:
* How can an LTL specified mission be scaled up to multiple robots operating in confined environments?
The Cooperative Multi-agent Planning Problem is addressed by borrowing a technique from cooperative pathfinding problems in discrete grid environments. Since centralized planning for multi-robot systems is computationally challenging and easily results in state space explosion, a distributed planning approach is provided through agent coupling and de-coupling.
In addition, in order to make such robot missions work in the real world, robots should take actions in the continuous physical world. Hence, in the second part of this thesis, the resulting motion planning problems is addressed for non-holonomic robots.
That is, it is devoted to autonomous vehicles’ motion planning in challenging environments such as rural, semi-structured roads. This planning problem is solved with an on-the-fly hierarchical approach, using a pre-computed lattice planner. It is also proved that the proposed algorithm guarantees resolution-completeness in such demanding environments. Finally, possible extensions are discussed.
The first part of this dissertation covers methods that resolve some instances of this mismatch when the mission requirements are expressed in Linear Temporal Logic (LTL) for handling coverage, sequencing, conditions and avoidance. That is, the following general questions are addressed:
* What cause of the given mission is unrealizable?
* Is there any other feasible mission that is close to the given one?
In order to answer these questions, the LTL Revision Problem is applied and it is formulated as a graph search problem. It is shown that in general the problem is NP-Complete. Hence, it is proved that the heuristic algorihtm has 2-approximation bound in some cases. This problem, then, is extended to two different versions: one is for the weighted transition system and another is for the specification under quantitative preference. Next, a follow up question is addressed:
* How can an LTL specified mission be scaled up to multiple robots operating in confined environments?
The Cooperative Multi-agent Planning Problem is addressed by borrowing a technique from cooperative pathfinding problems in discrete grid environments. Since centralized planning for multi-robot systems is computationally challenging and easily results in state space explosion, a distributed planning approach is provided through agent coupling and de-coupling.
In addition, in order to make such robot missions work in the real world, robots should take actions in the continuous physical world. Hence, in the second part of this thesis, the resulting motion planning problems is addressed for non-holonomic robots.
That is, it is devoted to autonomous vehicles’ motion planning in challenging environments such as rural, semi-structured roads. This planning problem is solved with an on-the-fly hierarchical approach, using a pre-computed lattice planner. It is also proved that the proposed algorithm guarantees resolution-completeness in such demanding environments. Finally, possible extensions are discussed.
ContributorsKim, Kangjin (Author) / Fainekos, Georgios (Thesis advisor) / Baral, Chitta (Committee member) / Lee, Joohyung (Committee member) / Berman, Spring (Committee member) / Arizona State University (Publisher)
Created2019
Description
A novel underwater, open source, and configurable vehicle that mimics and leverages advances in quad-copter controls and dynamics, called the uDrone, was designed, built and tested. This vehicle was developed to aid coral reef researchers in collecting underwater spectroscopic data for the purpose of monitoring coral reef health. It is designed with an on-board integrated sensor system to support both automated navigation in close proximity to reefs and environmental observation. Additionally, the vehicle can serve as a testbed for future research in the realm of programming for autonomous underwater navigation and data collection, given the open-source simulation and software environment in which it was developed. This thesis presents the motivation for and design components of the new vehicle, a model governing vehicle dynamics, and the results of two proof-of-concept simulation for automated control.
ContributorsGoldman, Alex (Author) / Das, Jnaneshwar (Thesis advisor) / Asner, Greg (Committee member) / Marvi, Hamidreza (Committee member) / Arizona State University (Publisher)
Created2020
Description
The objective of this project was to research and experimentally test methods of localization, waypoint following, and actuation for high-speed driving by an autonomous vehicle. This thesis describes the implementation of LiDAR localization techniques, Model Predictive Control waypoint following, and communication for actuation on a 2016 Chevrolet Camaro, Arizona State University’s former EcoCAR. The LiDAR localization techniques include the NDT Mapping and Matching algorithms from the open-source autonomous vehicle platform, Autoware. The mapping algorithm was supplemented by that of Google Cartographer due to the limitations of map size in Autoware’s algorithms. The Model Predictive Control for waypoint following and the computer-microcontroller-actuator communication line are described. In addition to this experimental work, the thesis discusses an investigation of alternative approaches for each problem.
ContributorsCopenhaver, Bryce Stone (Author) / Berman, Spring (Thesis director) / Yong, Sze Zheng (Committee member) / Dean, W.P. Carey School of Business (Contributor) / Engineering Programs (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
The scientific research conducted by science, technology, engineering, and mathematics (STEM) institutions is groundbreaking. Everyday, scientists create a deeper understanding of the world around us, and then communicate that understanding through journal papers, articles, and conferences. To strengthen these traditional forms of communication, science communicators can use social media platforms such as Twitter and Facebook to promote themselves and earn digital audience engagement that will grow the impact and success of their research. This thesis synthesizes research on human communication theories, digital user behavior, and science communication practices in order to create the “Science Communicator’s Guide to Social Media Engagement”. This guide empowers science communicators to utilize social media in a way that can increase their digital audience engagement, expand the reach of their research, and ultimately amplify their professional presence in the scientific community.
ContributorsVandekop, Victoria Margueritte (Author) / Asner, Greg (Thesis director) / Martin, Roberta (Committee member) / Hugh Downs School of Human Communication (Contributor) / Watts College of Public Service & Community Solut (Contributor) / Barrett, The Honors College (Contributor)
Created2020-12