A5023871411- Augmented Reality Applications
- Human-Automation Interaction and Safety
- Teaching and Learning Programming
- Human Pose and Action Recognition
- Social Robot Interaction and HRI
- Interactive and Immersive Displays
- AI in Service Interactions
- Human Motion and Animation
- Robotics and Sensor-Based Localization
- Artificial Intelligence in Games
- Experimental Learning in Engineering
- Advanced Neural Network Applications
- Robotic Path Planning Algorithms
- Robot Manipulation and Learning
- Optimization and Search Problems
- Multimodal Machine Learning Applications
- Robotics and Automated Systems
- Robotic Mechanisms and Dynamics
- Advanced Vision and Imaging
- Spreadsheets and End-User Computing
- Teleoperation and Haptic Systems
- Innovative Teaching Methods
- Advanced Manufacturing and Logistics Optimization
- Virtual Reality Applications and Impacts
- Software Testing and Debugging Techniques
University of North Carolina at Chapel Hill
2023-2024
University of Colorado Boulder
2022
The field of end-user robot programming seeks to develop methods that empower non-expert programmers task and modify operations. In doing so, researchers may enhance flexibility broaden the scope deployments into real world. We introduce PRogramAR (Programming Robots using Augmented Reality), a novel system combines intuitive visual feedback augmented reality (AR) with simplistic responsive paradigm trigger-action (TAP) facilitate human-robot collaboration. Through PRogramAR, users are able...
Programming robots is a challenging task exacer-bated by software bugs, faulty hardware, and environmental fac-tors. When coding issues arise, traditional debugging techniques such as output logs or print statements that may help in typical computer applications are not always useful for roboticists. As result, roboticists often leverage visualizations depict various aspects of robot, sensor, environment states. In this paper, we explore design approaches towards robotics support, including...
In this work, we present the design and evaluation of an immersive Cyber-Physical Control Room interface for remote mobile robots that provides users with both robot-egocentric robot-exocentric 3D perspectives. We evaluate room against a traditional robot in mock disaster response scenario features mixed human-robot field team. our evaluation, found improved operator effectiveness by 28% while navigating complex warehouse environment performing visual search. The also enhanced various...
The 6th International Workshop on Virtual, Augmented, and Mixed Reality for Human-Robot Interaction (VAM-HRI) will bring together HRI, robotics, mixed reality researchers to address challenges in interactions between humans robots. Topics relevant the workshop include development of robots that can interact with reality, use virtual developing interactive robots, design augmented interfaces mediate communication investigations robot learning, comparisons capabilities perceptions agents, best...
Robot Imitation Learning (IL) is a widely used method for training robots to perform manipulation tasks that involve mimicking human demonstrations acquire skills. However, its practicality has been limited due requirement users be trained in operating real robot arms provide demonstrations. This paper presents an innovative solution: Augmented Reality (AR)-assisted framework demonstration collection, empowering non-roboticist produce IL using devices like the HoloLens 2. Our facilitates...
The 7th International Workshop on Virtual, Augmented, and Mixed Reality for Human-Robot Interaction (VAM-HRI) seeks to bring together researchers from human-robot interaction (HRI), robotics, mixed reality (MR) address the challenges related interactions between humans robots. Key topics include development of robots capable interacting with in reality, use virtual creating interactive robots, designing augmented interfaces communication exploring enhancing robot learning, comparative...
Lab assignments, in which students build and program robots to accomplish tasks various environments, are a central component many undergraduate robotics classes. Such activities require that operationalize concepts learned class. However, physical prone uncertain real-world behavior, making debugging challenging causing feel stressed about being graded based on their robot's performance. Therefore, we incorporated retakes into our class, allowing learn from mistakes master class content...
Robot Imitation Learning (IL) is a crucial technique in robot learning, where agents learn by mimicking human demonstrations. However, IL encounters scalability challenges stemming from both non-user-friendly demonstration collection methods and the extensive time required to amass sufficient number of demonstrations for effective training. In response, we introduce Augmented Reality Collection generAtion DEmonstrations (ARCADE) framework, designed scale up manipulation tasks. Our framework...
Educational robotics, in which students program a physical robot to interact with the real world, can provide tangible active learning opportunities that are often linked increases student computational thinking, creativity, and motivation. To date, ER has focused on use of robots augment adjacent fields (e.g., mathematics, programming, digital media) for K--12 students. As result, we lack guidelines for: (1) supporting college robotics discipline itself (2) students, who may possess...
Programming robots is a challenging task exacer-bated by software bugs, faulty hardware, and environmental factors. When coding issues arise, traditional debugging techniques are not always useful for roboticists. Robots often have an array of sensors that output complex data, which can be difficult to decipher as raw text. Augmented reality (AR) provides unique medium conveying data the user displaying information directly in scene their corresponding visual definition. In my research, I am...
This technical report summarizes submissions and compiles from Actor-Action video classification challenge held as a final project in CSC 249/449 Machine Vision course (Spring 2020) at University of Rochester