2026 ASEE Annual Conference & Exposition

Closing the Adoption Gap: AI-driven, Low-Latency, and Compatible Remote Robotics Laboratories

Presented at Engineering Technology Division (ETD) Technical Session 8

The paper presents a work-in-progress educational teleoperation platform designed to support remote and hybrid robotics laboratories by addressing a key challenge in instructional teleoperation systems: end-to-end latency. The platform enables students to control a physical robot remotely while interacting with a synchronized robot digital twin, providing hands-on learning experiences for both distance and in-person learners. The system employs a lightweight, latency-aware predictive control framework based on pre-recorded user motion trajectories and adaptive control. User arm motions are captured through wearable sensing and mapped to joint-level commands that drive both the simulated robot and a physical robot concurrently. When tracking error exceeds a predefined threshold, a prediction algorithm selectively activates, using pre-recorded user commands as reference trajectories to compensate for communication and actuation delays. This approach reduces perceived latency while maintaining stability and simplicity, making it suitable for undergraduate engineering technology laboratories. The platform integrates a digital twin implemented in simulation software with a low-cost physical robot controlled through a microcontroller-based interface. Latency is explicitly measured across user input, simulation, physical actuation, and feedback stages to evaluate synchronization between systems. The implementation was embedded within an undergraduate robotics laboratory course, where students conducted repeated teleoperation trials using arm motion to control both the physical robot and its digital twin. Preliminary experimental results demonstrate a reduction in perceived command-to-actuation lag when prediction is enabled, along with improved tracking accuracy. Educational effectiveness was evaluated through post-lab student surveys included in course assessments, focusing on usability, learning effectiveness, and relevance to workforce preparation and advanced study. Survey results indicate strong student agreement regarding the platform’s ease of use, learning value, and feasibility for remote laboratory instruction. While this study does not yet incorporate immersive reality interfaces, computer vision pipelines, or learning-based intent prediction, these components are planned as future extensions. Overall, this work establishes a cost-effective, scalable proof-of-concept for teleoperation-enabled remote laboratories, aligned with engineering technology education objectives related to applied learning, modern tool usage, and equitable access to hands-on robotics education.

Authors

Dr. Meenakshi Narayan Miami University [biography]

Dr. Meenakshi Narayan is currently an assistant professor and the department coordinator for robotics engineering technology at Miami University, a position she has held since the fall of 2021. She earned her Ph.D. in Mechanical Engineering from the University of Texas at Dallas in December 2020. Dr. Narayan's doctoral research was centered on the development of robust predictive control models designed to enhance patient safety during robotic interventional procedures. Her research interests encompass a wide range of areas, including dynamics systems and control, teleoperation, haptics, data-driven models, signal processing, and artificial intelligence. She applies her expertise in these domains to address challenges in healthcare and industrial automation. At Miami University, Dr. Narayan instructs courses related to electrical engineering technology and is actively involved in the creation of innovative robotics courses for the Bachelor of Technology in Robotics program. These efforts involve collaboration with industry partners and are backed by support from university endowments and funding from the Ohio Department of Higher Education. Her overarching goal is to modernize and invigorate the engineering technology curriculum to prepare students for the demands of the future workforce, aligning with the evolving needs of the industry.
Moataz M. Salem Miami University
Lokesh Kumar Saharan http://orcid.org/0000-0001-9032-4137 Gannon University [biography]

Dr. Lokesh Saharan is currently serving as an Assistant Professor of Mechanical Engineering within the Department of Mechanical Engineering at the College of Engineering and Business at Gannon University. He obtained his Ph.D. from the University of Texas at Dallas in December 2017. Dr. Saharan's research interests encompass various fields, including engineering education, rehabilitation robotics, smart materials, soft robotics, and additive manufacturing. His academic contributions include multiple research articles published in peer-reviewed journals and conferences, as well as a book chapter. In addition to his research work, he has actively participated as a reviewer for various peer-reviewed conferences and journals.
Before joining Gannon University, Dr. Saharan held the position of Assistant Professor and Department Coordinator for Mechanical Engineering at the University of Texas Permian Basin. During this time, he established and managed the Advanced Manufacturing Center, which received substantial funding of $1.1 million from the Odessa Development Corporation. He also served as a co-principal Investigator for a Department of Education EM-Step grant valued at $750,000.
Further enriching his academic journey, Dr. Saharan contributed as an Assistant Teaching Professor at Penn State Behrend during the academic year 2019-20. Here, he played a pivotal role in developing new courses for the biomedical minor within the Mechanical Engineering department. Prior to his tenure in the United States, Dr. Saharan held the position of Assistant Professor (Instruction) in the Mechanical Engineering department at the National Institute of Technology Kurukshetra in India.
Throughout his academic and research career, Dr. Saharan has made significant contributions in both teaching and research roles, spanning multiple countries and institutions.

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