My research involves Robotics, Autonomous Systems, and AI. I focus on developing intelligent decision-making models to navigate/control robots using AI methods.
I'm interested in topics related to the AI and robotics integration, including Computer Vision, Deep Learning, Large Language Models, Reinforcement Learning, Robot Learning, and Tranfer Learning.
I'm currently pursuing the following projects:
🖥 + 👃 + 🤖 AI-based Odor Source Localization
This project leverages various AI techniques to design a navigation model to guide a robot in finding a hidden odor source location with onboard vision and olfaction sensors.
🌲 + 🔥 + ✈ Wildfire Early Detection with Unmanned Aerial Vehicles
The core of this project is to integrate Computer Vision and Robotic Olfaction to enable a robot (i.e., a drone) "see" and "smell" the environment to detect early wildfire locations.
🤖 + + 🤖 Multi-Agent Collaboration and Robot Localization
This project involves designing Multi-Agent Collaboration Algorithms for controlling a fleet of robots and Sensor Data Fusion Algorithms for Robot Localization.
2024
📝 04-05-2024: Our paper, entitled "Robotic Odor Source Localization via Vision and Olfaction Fusion Navigation Algorithm", is published on Sensors.
📝 04-04-2024: Our paper, entitled "Deep Learning-based Wildfire Smoke Detection using Uncrewed Aircraft System Imagery", is accepted on IEEE UR 2024.
🔍 04-02-2024: Our project, entitled "Advancing Embodied AI for Enhanced Robotic Odor Source Localization", is recommended to be funded by Louisiana Board of Regent for 3 years $108K.
🎤 01-12-2024: I give a research talk, entitled "Robotic Odor Source Localization via AI Methods", at the CAR Lab of University of Delaware. Thanks for Dr. Weisong Shi's hosting!
2023
📝 12-11-2023: Our two papers, entitled "Multi-modal Robotic Platform Development for Odor Source Localization" and "Robotic Odor Source Localization via End-to-End Recurrent Deep Reinforcement Learning", are accepted on IEEE IRC 2023 Conference.
📝 06-25-2023: Our paper, entitled "Vision and Olfactory-Based Wildfire Monitoring with Uncrewed Aircraft Systems", is accepted at the IEEE UR 2023.
📝 04-01-2023: Our paper, entitled "Learn to Trace Odors: Robotic Odor Source Localization via Deep Learning Methods with Real-world Experiments", is accepted at the IEEE SoutheastCon 2023.
📝 02-06-2023: Our paper, entitled "Autonomous Underwater Vehicle Based Chemical Plume Tracing via Deep Reinforcement Learning Methods", is published on Journal of Marine Science and Engineering.
2022
🎉 09-01-2022: I start a new position of Assistant Professor of Electrical Engineering at Louisiana Tech University.
Proposed a Hierachical Control framework to control a robot finding the odor source by coordinating obstacle avoidance, vision-based navigation, and olfaction-based navigation behaviors.
Improved the traditional moth-inspired odor source localization algorithm with a fuzzy inference system to adaptively change search parameters and behaviors.
Designed a robot navigation algorithm for finding a hidden odor source. Two steps are involved: 1. Source & Plume Mapping (fuzzy inference) 2. Path Planning (RL).
Presented a new vision-based wildfire smoke detection from drone's imageries, which involves image segmentationa and object detection to reduce the false alarm rate.
Implemented Extended Kalman Filter and Unscented Kalman Filter to determine AUV locations based on IMU (acceleration), Doppler Velocity Log (velocity), and Short Baseline (position) measurements.
I'm teaching courses related to Control Theorems, Artificial Intelligence, and Robotics. These are the courses that I offer per year:
ELEN 471: Autonomatic Control Systems - Every Fall 🍂
ELEN 472/572: Introduction to Digital Control Systems - Every Winter
ELEN/CSC 451: Hands-on Artificial Intelligence and Robotics - Every Spring 🌱
My latest teaching evaluation reports can be accessed via the following links:
