Brief Research Overview  

The SMART Lab is an interdisciplinary lab consisting of members with diverse academic and research backgrounds, including 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 to apply them to field robotics and to assistive technology and robotics. We have gained broad hands-on experience in the software and hardware aspects of robot design and control by creating various types of robotic and autonomous systems, ranging from mobile robots, aquatic robots, and assistive robotic systems. Most of our robots are low-cost and open-source-based (SMART Lab GitHub) and are designed to offer opportunities for end users who are interested in robots, but have been priced out by high costs.

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 in many respects. For example, they allow researchers in the robotics field to conduct real experiments, advancing their research in a more practical and efficacious way, and they enable K-12 and college students to participate in hand-on activities and so learn robotics more effectively. They also offer opportunities for end users who are interested in robots, but have been priced out by high costs. However, only a very few low-cost, open-source robotic platforms are currently available. The SMART Lab is applying software and hardware development experience accumulated over many years to develop a variety of robot types, such as mobile and aquatic robots, that are inexpensive 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)

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Description:  All life depends on water, and we are all citizens of watersheds; however, human activities often lead to contamination that can disrupt and disorganize both biological and social communities. Moreover, contamination of sediments with pollutants such as heavy metals can damage habitats for fish and other aquatic life, and even affect human health. Belated recognition of a water crisis can incur tremendous costs and require considerable recovery time, and also foster social and political strife. As such, there is great benefit in regular monitoring of water and sediment quality through sampling activities. The SMART Lab is currently developing a novel cyber-physical system for water and sediment sampling, integrating control software and mobile robots to conduct autonomous monitoring and analysis. Overall, our research will increase knowledge 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 when monitoring water quality. We believe these contributions will significantly enhance 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