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- Creators: Barrett, The Honors College
- Creators: Bush, Jonathan Ernest
Description
As robotics technology advances, robots are being created for use in situations where they collaborate with humans on complex tasks. For this to be safe and successful, it is important to understand what causes humans to trust robots more or less during a collaborative task. This research project aims to investigate human-robot trust through a collaborative game of logic that can be played with a human and a robot together. This thesis details the development of a game of logic that could be used for this purpose. The game of logic is based upon a popular game in AI research called ‘Wumpus World’. The original Wumpus World game was a low-interactivity game to be played by humans alone. In this project, the Wumpus World game is modified for a high degree of interactivity with a human player, while also allowing the game to be played simultaneously by an AI algorithm.
ContributorsBoateng, Andrew Owusu (Author) / Sodemann, Angela (Thesis director) / Martin, Thomas (Committee member) / Software Engineering (Contributor) / Engineering Programs (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
Description
As robots become more prevalent, the need is growing for efficient yet stable control systems for applications with humans in the loop. As such, it is a challenge for scientists and engineers to develop robust and agile systems that are capable of detecting instability in teleoperated systems. Despite how much research has been done to characterize the spatiotemporal parameters of human arm motions for reaching and gasping, not much has been done to characterize the behavior of human arm motion in response to control errors in a system. The scope of this investigation is to investigate human corrective actions in response to error in an anthropomorphic teleoperated robot limb. Characterizing human corrective actions contributes to the development of control strategies that are capable of mitigating potential instabilities inherent in human-machine control interfaces. Characterization of human corrective actions requires the simulation of a teleoperated anthropomorphic armature and the comparison of a human subject's arm kinematics, in response to error, against the human arm kinematics without error. This was achieved using OpenGL software to simulate a teleoperated robot arm and an NDI motion tracking system to acquire the subject's arm position and orientation. Error was intermittently and programmatically introduced to the virtual robot's joints as the subject attempted to reach for several targets located around the arm. The comparison of error free human arm kinematics to error prone human arm kinematics revealed an addition of a bell shaped velocity peak into the human subject's tangential velocity profile. The size, extent, and location of the additional velocity peak depended on target location and join angle error. Some joint angle and target location combinations do not produce an additional peak but simply maintain the end effector velocity at a low value until the target is reached. Additional joint angle error parameters and degrees of freedom are needed to continue this investigation.
ContributorsBevilacqua, Vincent Frank (Author) / Artemiadis, Panagiotis (Thesis director) / Santello, Marco (Committee member) / Trimble, Steven (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)
Created2013-05
Description
I compared scores of situational awareness to mission performance scores from the Human-Robot Interaction Lab at the ASU campus. This study uses Roblox in a virtual environment to simulate a search and rescue environment. Higher situational awareness was seen to be positively correlated with mission performance scores, but the study is yet to be complete.
ContributorsHartman, Miles (Author) / Cooke, Nancy (Thesis director) / Chiou, Erin (Committee member) / Barrett, The Honors College (Contributor) / Human Systems Engineering (Contributor)
Created2023-05
Description
Riding a bicycle requires accurately performing several tasks, such as balancing and navigation, which may be difficult or even impossible for persons with disabilities. These difficulties may be partly alleviated by providing active balance and steering assistance to the rider. In order to provide this assistance while maintaining free maneuverability, it is necessary to measure the position of the rider on the bicycle and to understand the rider's intent. Applying autonomy to bicycles also has the potential to address some of the challenges posed by traditional automobiles, including CO2 emissions, land use for roads and parking, pedestrian safety, high ownership cost, and difficulty traversing narrow or partially obstructed paths.
The Smart Bike research platform provides a set of sensors and actuators designed to aid in understanding human-bicycle interaction and to provide active balance control to the bicycle. The platform consists of two specially outfitted bicycles, one with force and inertial measurement sensors and the other with robotic steering and a control moment gyroscope, along with the associated software for collecting useful data and running controlled experiments. Each bicycle operates as a self-contained embedded system, which can be used for untethered field testing or can be linked to a remote user interface for real-time monitoring and configuration. Testing with both systems reveals promising capability for applications in human-bicycle interaction and robotics research.
The Smart Bike research platform provides a set of sensors and actuators designed to aid in understanding human-bicycle interaction and to provide active balance control to the bicycle. The platform consists of two specially outfitted bicycles, one with force and inertial measurement sensors and the other with robotic steering and a control moment gyroscope, along with the associated software for collecting useful data and running controlled experiments. Each bicycle operates as a self-contained embedded system, which can be used for untethered field testing or can be linked to a remote user interface for real-time monitoring and configuration. Testing with both systems reveals promising capability for applications in human-bicycle interaction and robotics research.
ContributorsBush, Jonathan Ernest (Author) / Zhang, Wenlong (Thesis advisor) / Heinrichs, Robert (Thesis advisor) / Sandy, Douglas (Committee member) / Arizona State University (Publisher)
Created2020
Description
Each year, the average vehicle contributes 4.6 metric tons of carbon dioxide into the atmosphere [1]. These gases contribute to around 30,000 premature deaths each year [2] and are linked to in the increase in cases of Asthma. Human health is further impacted by the increase of greenhouse gasses in the atmosphere. Rays from the sun travel to the Earth where they are absorbed. Absorbing the sun’s rays heats up the Earth which is then radiated into space. Greenhouse gasses inhibit this process much like the glass walls in a greenhouse. As a result, the temperature of the Earth steadily increases. The greenhouse effect is dangerous because it can be linked to natural disasters, rising ocean levels, and extinction of species. One of the biggest contributors to the greenhouse effect is burning fossil fuels. Powerplants, agriculture, and transportation are some of the largest contributors to the increase of atmospheric carbon dioxide. To mitigate the effects of transportation, car companies have invested into production of alternative and renewable fuels for their products. One of the sources which has gained popularity recently, is the use of electricity to power our vehicles. Tesla has spearheaded the electric car movement and is largely responsible for this beneficial shift. One issue with this approach is that a majority, around 76.3%, of Americans drive alone on their commute [13]. The market in its current state encourages inefficient transportation due to the lack of alternatives. While motorcycles may offer a more eco-friendly and economical approach to cars, many are afraid of potential hazards of using this mode of transportation. The introduction of electric bikes offers an interesting approach to improving this efficiency and safety issue. The wide availability to customers offers an alternative which pushes the traditional distance limits for commuting on a bicycle. Since the market is relatively new, several issues pose challenges to consumers. This research aims to clarify and analyze the electric bike market in order to supply a potential customer with the tools needed to acquire a high quality and reasonably price bike.
ContributorsFriedrich, Collin Anthony (Author) / Lee, Hyunglae (Thesis director) / Lacy, Gerald (Committee member) / Mechanical and Aerospace Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
Bicycles are already used for daily transportation by a large share of the world's population and provide a partial solution for many issues facing the world today. The low environmental impact of bicycling combined with the reduced requirement for road and parking spaces makes bicycles a good choice for transportation over short distances in urban areas. Bicycle riding has also been shown to improve overall health and increase life expectancy. However, riding a bicycle may be inconvenient or impossible for persons with disabilities due to the complex and coordinated nature of the task. Automated bicycles provide an interesting area of study for human-robot interaction, due to the number of contact points between the rider and the bicycle. The goal of the Smart Bike project is to provide a platform for future study of the physical interaction between a semi-autonomous bicycle robot and a human rider, with possible applications in rehabilitation and autonomous vehicle research.
This thesis presents the development of two balance control systems, which utilize actively controlled steering and a control moment gyroscope to stabilize the bicycle at high and low speeds. These systems may also be used to introduce disturbances, which can be useful for studying human reactions. The effectiveness of the steering balance control system is verified through testing with a PID controller in an outdoor environment. Also presented is the development of a force sensitive bicycle seat which provides feedback used to estimate the pose of the rider on the bicycle. The relationship between seat force distribution is demonstrated with a motion capture experiment. A corresponding software system is developed for balance control and sensor integration, with inputs from the rider, the internal balance and steering controller, and a remote operator.
This thesis presents the development of two balance control systems, which utilize actively controlled steering and a control moment gyroscope to stabilize the bicycle at high and low speeds. These systems may also be used to introduce disturbances, which can be useful for studying human reactions. The effectiveness of the steering balance control system is verified through testing with a PID controller in an outdoor environment. Also presented is the development of a force sensitive bicycle seat which provides feedback used to estimate the pose of the rider on the bicycle. The relationship between seat force distribution is demonstrated with a motion capture experiment. A corresponding software system is developed for balance control and sensor integration, with inputs from the rider, the internal balance and steering controller, and a remote operator.
ContributorsBush, Jonathan Ernest (Author) / Zhang, Wenlong (Thesis director) / Sandy, Douglas (Committee member) / Software Engineering (Contributor, Contributor) / Engineering Programs (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05