Research Overview

Adaptive Human Multi-robot Systems


Description:  This project develops adaptive human multi-robot systems that can flexibly respond to changes in situation and task needs. It develops methods for real-time monitoring and analysis of the cognitive and emotional state of operators, enabling human operators to adapt to robot system changes and robots to adapt to human cognitive and emotional states. By developing adaptive systems to improve the performance of human-robot teams, the project advances our understanding of human multi-robot interactions. The new technologies provided will improve function of human multi-robot teams deployed (for example) in environmental monitoring, nuclear cleanup, disaster response, and defense. The project advances STEM education and workforce development by involving K-12 students, undergraduate and graduate women, minorities, and underrepresented groups in human-robot interaction and multi-robot systems.

Grants: NSF
People: Wonse Jo, Ahreum Lee, Tamzidul Mina, Jeremy Pan, Yuta Hoashi , Walter Kruger
Project Website: (Under Development)

Selected Publications:

  • Tamzidul Mina, Maliha Hossain, Jee Hwan Park, and Byung-Cheol Min, "Efficient Resource Distribution by Adaptive Inter-agent Spacing in Multi-agent Systems", 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC), Bari, Italy, 6-9 October, 2019. Download Video
  • Wonse Jo, Jee Hwan Park, Sangjun Lee, Ahreum Lee, and Byung-Cheol Min, "Design of a Human Multi-Robot Interaction Medium of Cognitive Perception", 2019 ACM/IEEE International Conference on Human-Robot Interaction - Late Breaking Reports (LBR), Daegu, South Korea, March 11-14, 2019. Download Video
Autonomous Robotic Teams for a Real-Time Water Monitoring


Description:  Water monitoring is an important task to conserve natural resources such as rivers and lakes. For a long period of time water monitoring methods have been based on the human activities. For example, water sampling is the most common human activity. However, this technique entails some inherent disadvantages. In case of a large river with fast flow, it is dangerous to the samplers. Moreover, it is slow and costly because human samplers should travel to sites for conducting a water sampling on their own. Also, it is inefficient for a long-term and real-time monitoring. Recently, autonomous water monitoring systems composed of mobile sensors for real time monitoring and data collection have been introduced. Unmanned Aerial Vehicle (UAV) and Unmanned Surface Vehicle (USV) are proposed to overcome the disadvantages of the human based methods.
   The goal of this research is to develop a continuous, real-time autonomous river monitoring system. We are planning to develop the autonomous robotic teams that integrate a variety of technologies including robots, crowdsourcing, advanced region of interest (ROI) selection and path planning. For this research ‘Wabash River’ is the targeted test site because it is the one of the longest rivers in the US and main stream in Indiana state. This research is at the beginning stage. Based on the needs assessment, this system will be iteratively designed to be fully capable of various tasks, such as water sampling, water pollution monitoring, sediment sampling, and early flood warning.

Grants: NSF, UNSA, Purdue University
People: Yogang Singh, Jun Han Bae, Wonse Jo, Shaocheng Luo, Jee Hwan Park, Yuta Hoashi
Project Website:

Selected Publications:

  • Jun Han Bae, Wonse Jo, Jee Hwan Park, Richard M. Voyles, and Byung-Cheol Min, "Sediment Sampling Methods for an Autonomous Water Quality Monitoring System", IEEE Journal of Oceanic Engineering. (Under Review)
  • Wonse Jo, Yuta Hoashi, Lizbeth Leonor Paredes Aguilar, Mauricio Postigo-Malaga, José Garcia-Bravo, and Byung-Cheol Min, "A Low-cost Small USV Platform for Water Quality Monitoring", HardwareX, 2019. (In press)
  • Jun Han Bae, Jeehwan Park, Sangjun Lee, and Byung-Cheol Min, "Tri-SedimentBot: An Underwater Sediment Sampling Robot", Automation Science and Engineering (CASE), 2016 IEEE International Conference on, Fort Worth, Texas, USA, Aug. 21-24, 2016. Download PDF, Download Video
Distributed Rendezvous and Formation Control in Cluttered Environments

Description: We consider the rendezvous problem as robots exploring the unknown environment with minimum communication and arrive at the selected rendezvous location. The problem of rendezvous is ubiquitous in nature. Animals in migration are able to share information about food and water thus the whole group rendezvous at those locations. Human also have same issue as we need to meet specific people in specific place, which is applied still in multi-agent robotic systems. With emerging technologies such as localization, ubiquitous wireless communication, and advanced computation capability, enhanced rendezvous control shall bring wider application scenarios like intelligent warehouse and urban search and rescue. The purpose of this research is to develop a bounded distributed rendezvous control mechanism in cluttered environment. The robots within this environment have basically none knowledge of the environment, but can rendezvous at the destination while conquering the limitations such as communication being blocked by large obstacles, and path blocked by small obstacles, with proper decision making mechanism and obstacle avoidance algorithms. Meanwhile, the efficiency in rendezvous is also considered, we try to figure out robotic rendezvous control which not only handles communication unavailable occasions and obstacle avoidance, but also maintain an efficiency-prior trajectory.

Grants: NSF, Purdue University
People: Shaocheng Luo, Jun Han Bae

Selected Publications:

  • Shaocheng Luo and Byung-Cheol Min, "Algae Harvesting with a Multi-robot Team", IEEE Transactions on Systems, Man, and Cybernetics: Systems. (Under Review)
  • Shaocheng Luo, Jonghoek Kim, Ramviyas Parasuraman, Jun Han Bae, Eric T. Matson, and Byung-Cheol Min, "Multi-robot Rendezvous Based on Bearing-aided Hierarchical Tracking of Network Topology", Ad Hoc Networks, Vol. 86, pp. 131-143, April 2019. Download PDF, Download Video
  • Shaocheng Luo, Jun Han Bae, and Byung-Cheol Min, "Pivot-based Collective Coverage Control with a Multi-robot Team", 2018 IEEE International Conference on Robotics and Biomimetics (IEEE ROBIO 2018), Kuala Lumpur, Malaysia, December 12-15, 2018. Download Video
  • Ramviyas Parasuraman and Byung-Cheol Min, "Consensus Control of Distributed Robots Using Direction of Arrival of Wireless Signals", International Symposium on Distributed Autonomous Robotic Systems 2018 (DARS 2018), Boulder, CO, USA, Oct 15-17, 2018. Source Codes, Download Video
  • Ramviyas Parasuraman, Jonghoek Kim, Shaocheng Luo, and Byung-Cheol Min, "Multi-Point Rendezvous in Multi-Robot Systems", IEEE Transactions on Cybernetics, Early Access, September, 2018. Download PDF, Download Video
Social Behavior in Multi-robot Systems


Description: Individuals can benefit in a social group by looking out for one another for support and survival. It is a proven phenomenon in nature and in this research our goal is to apply the same principles in a multi-robot system to improve robot survivability robustness.
   Traditionally, research on multi-robot systems has focused on developing application specific control algorithms while adapting individual robots in the group to operational environments and specific tasks without explicitly considering the advantages of being in a social group. However, given the unpredictable nature of various operational environments and autonomous mission requirements, designing individual robots that can take into account all possible scenarios is unfeasible, expensive and still lack robustness in survivability. In contrast, we believe introducing a social group aspect to the multi-robot system may provide a unique and robust way of dealing with such cases.
   For our initial work, social behavioral inspiration was taken from the Huddling behavior of Emperor Penguins in the Antarctic where they share body heat and take turns being in the huddle centers to survive conditions as severe as Antarctic winters as a group.
   Potential research on the topic include energy sharing between heterogeneous robotic agents, application of machine learning techniques for distributed position shuffling within the group to survive damaging external stimuli, distributed control techniques for cooperative object transportation specifically focusing on minimal individual health loss for long term survival of the multi-robot system.

Grants: Purdue University
People: Tamzidul Mina

Selected Publications:

  • Tamzidul Mina and Byung-Cheol Min, "Penguin Huddling Inspired Distributed Boundary Movement for Group Survival in Multi-robot Systems using Gaussian Processes", 2018 IEEE International Conference on Robotics and Biomimetics (IEEE ROBIO 2018), Kuala Lumpur, Malaysia, December 12-15, 2018. Download Video
  • Tamzidul Mina and Byung-Cheol Min, "Penguin Huddling-inspired Energy Sharing and Formation Movement in Multi-robot Systems", 2018 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), Philadelphia, PA, USA, August 6-8, 2018. Download PDF, Download Video
Reliability and Safety of Autonomous Multi-Agent Systems

Description: Today's autonomous cars, otherwise known as driverless vehicles or self-driving cars, enable the deployment of safety technologies, such as collision warning, automatic emergency braking, and Vehicle-to-Vehicle technologies. In the near future, these systems in all vehicles will help to achieve zero fatalities, zero injuries, and zero accidents. However, behind the potential of these innovations, there is new challenge on autonomous cars that still need to address: cybersecurity.
   As the first step, we propose an attack-aware multi-sensor integration algorithm for the navigation system. A Fault Detection and Isolation (FDI) scheme is adopted for the detection of cyberattacks on navigation systems. Particularly, a discrete Extended Kalman Filter (EKF) is employed to construct robust residuals in the presence of noise. The proposed method uses a parametric statistical tool for detecting attacks based on the residuals in properties of discrete time signals and dynamic systems. It is based on a measurement history rather than a single measurement at a time. These approaches enable the proposed multi-sensor integration algorithm to generate a quick detection and low false alarms rate that are suitable to the applications of dynamic systems. Finally, as a case study, INS/GNSS integration for autonomous vehicle navigation systems is considered and tested with software-in-the-loop simulation (SILS).
   In addition, we consider attack detection algorithms autonomous multi-vehicle systems with imperfect information. This research addresses how a locally controlled autonomous agent can be identified by other agents if it has been compromised and how to make decisions with the ultimate goal of recovering system functionality and safety.

Grants: NIJ
People: Sangjun Lee

Selected Publications:

  • Sangjun Lee and Byung-Cheol Min, "Distributed Direction of Arrival Estimation-aided Cyberattack Detection in Networked Multi-Robot Systems", 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2018), Madrid, Spain, October 1-5, 2018. Download Video
  • Sangjun Lee, Yongbum Cho, and Byung-Cheol Min, "Attack-aware Multi-sensor Integration Algorithm for Autonomous Vehicle Navigation Systems", 2017 IEEE International Conference on Systems, Man and Cybernetics (SMC), Banff, Canada, 5-8 October, 2017. Download PDF, Download Video