Brief Research Overview  

The SMART Lab is an interdisciplinary research group made up of members with diverse backgrounds in fields such as robotics, computing, electrical engineering, control engineering, and mechanical engineering. This uniqueness plays a pivotal role in designing, modelling and controlling new robots, and developing algorithms and systems for their practical application in field robotics and assistive technology. Our team has extensive experience in both the software and hardware aspects of robot design and control, by creating a range of new robotic and autonomous systems including mobile robots, aquatic robots, and assistive robotic systems. Many of these systems are low-cost and open-source (SMART Lab GitHub), making them accessible to a wider range of users who may have been priced out by more expensive options.

You can learn more about our current and past research on robot design and control below.

Low-cost and Open-source Robot Platforms (2017 - Present)

   

Description:  Low-cost, open-source-based robotic platforms have great value and potential for a variety of purposes. For instance, they enable researchers in the field of robotics to conduct practical experiments, thereby advancing their research more effectively. Additionally, they allow K-12 and college students to engage in hands-on activities and learn about robotics more effectively. These platforms also provide opportunities for end users who are interested in robots but have been priced out due to high costs. However, there are currently only a few available low-cost, open-source robotic platforms. The SMART Lab is using its accumulated software and hardware development experience to create various types of robots, such as mobile and aquatic robots, that are affordable and easy for anyone to build. We share all our source code and hardware-related materials through online repositories such as GitHub.

Grants: NSF, UNSA, Purdue University
People: Wonse Jo, Pou Hei Chan, Jaeeun Kim, Jee Hwan Park, Yuta Hoashi

Selected Publications:

  • Wonse Jo, Jaeeun Kim, and Byung-Cheol Min, "ROS2 Open-Source Swarm Robot Platform: SMARTmBot", 2021 International Conference on Robotics and Automation (ICRA), Workshop on Robot Swarms in the Real World: From Design to Deployment - Live Demonstration, Xi'an, China, May 30 - June 5, 2021. Paper Link, GitHub Link, Video Link
  • Jun Han Bae, Shaocheng Luo, Shyam Sundar Kannan, Yogang Singh, Bumjoo Lee, Richard M. Voyles, Mauricio Postigo-Malaga, Edgar Gonzales Zenteno, Lizbeth Paredes Aguilar, and Byung-Cheol Min, "Development of an Unmanned Surface Vehicle for Remote Sediment Sampling with a Van Veen Grab Sampler", 2019 MTS/IEEE OCEANS, Seattle, WA, USA, October 27-31, 2019. Paper Link, Video Link
  • Wonse Jo, Jee Hwan Park, Yuta Hoashi, and Byung-Cheol Min, "Development of an Unmanned Surface Vehicle for Harmful Algae Removal", 2019 MTS/IEEE OCEANS, Seattle, WA, USA, October 27-31, 2019. Paper Link, Video Link
  • Wonse Jo, Yuta Hoashi, Lizbeth Leonor Paredes Aguilar, Mauricio Postigo-Malaga, José Garcia-Bravo, and Byung-Cheol Min, "A Low-cost and Small USV Platform for Water Quality Monitoring", HardwareX, Vol. 6, e00076, October 2019. Paper Link, Video Link , Source Codes Link
Water Quality Monitoring and Sediment Sampling (2016 - 2022)

sampler1

Description:  All life depends on water, and we are all part of watersheds. However, human activities can often lead to contamination that disrupts and damages both biological and social communities. Contamination of sediments with pollutants such as heavy metals can harm aquatic habitats and even affect human health. Late recognition of a water crisis can be costly and require significant recovery time, and can also create social and political conflict. Therefore, regular monitoring of water and sediment quality through sampling is crucial. The SMART Lab is currently developing a novel cyber-physical system for water and sediment sampling, combining control software and mobile robots to conduct autonomous monitoring and analysis. Our research will improve our understanding of how to effectively sample water and sediments with robotic systems and verify the ability of cyber-physical systems to enable real-time data processing in water quality monitoring. We believe these efforts will significantly advance the state-of-the-art in robotic environmental monitoring.

Grants: NSF, UNSA, Purdue University
People: Jun Han Bae, Pou Hei Chan, Shaocheng Luo, Wonse Jo, Yogang Singh, Yuta Hoashi
Project Website: https://engineering.purdue.edu/PRWQ

Selected Publications:

  • Jun Han Bae, Wonse Jo, Jee Hwan Park, Richard M. Voyles, Sara K. McMillan and Byung-Cheol Min, "Evaluation of Sampling Methods for Robotic Sediment Sampling Systems", IEEE Journal of Oceanic Engineering, Vol. 46, No. 2, pp. 542-554, April 2021. Paper Link, Video Link
  • Jun Han Bae, Shaocheng Luo, Shyam Sundar Kannan, Yogang Singh, Bumjoo Lee, Richard M. Voyles, Mauricio Postigo-Malaga, Edgar Gonzales Zenteno, Lizbeth Paredes Aguilar, and Byung-Cheol Min, "Development of an Unmanned Surface Vehicle for Remote Sediment Sampling with a Van Veen Grab Sampler", 2019 MTS/IEEE OCEANS, Seattle, WA, USA, October 27-31, 2019. Paper Link, Video Link
  • Wonse Jo, Jee Hwan Park, Yuta Hoashi, and Byung-Cheol Min, "Development of an Unmanned Surface Vehicle for Harmful Algae Removal", 2019 MTS/IEEE OCEANS, Seattle, WA, USA, October 27-31, 2019. Paper Link, Video Link
  • Shaocheng Luo, Yogang Singh, Hanyao Yang, Jun Han Bae, J. Eric Dietz, Xiumin Diao, and Byung-Cheol Min, "Image Processing and Model-Based Spill Coverage Path Planning for Unmanned Surface Vehicles", 2019 MTS/IEEE OCEANS, Seattle, WA, USA, October 27-31, 2019. Paper Link
  • Wonse Jo, Yuta Hoashi, Lizbeth Leonor Paredes Aguilar, Mauricio Postigo-Malaga, José Garcia-Bravo, and Byung-Cheol Min, "A Low-cost and Small USV Platform for Water Quality Monitoring", HardwareX, Vol. 6, e00076, October 2019. Paper Link, Video Link , Source Codes Link