Research
In DSA research group, we find new and creative approaches on synergizing the individual robots’ core capabilities and strengthening autonomy of robotic groups in order to solve large-scale problems, otherwise impossible with individual robots. We imagine such advancements in robotics science and engineering will build smarter cities where robots collect sensor data and act for modeling and curbing the spread of disease, improve the infrastructure of services, and ensure people’s sustainable living. Please follow the links below to learn more about the currently ongoing projects.
With advancements in sensing, actuation, and mechanical design, robots are becoming increasingly capable of performing complex and high-precision tasks, ranging from autonomous driving in urban areas to handling packages in fulfillment centers. The control and planning of robot motion in real-world environments demand high-fidelity models to simulate how the robot's movements affect physical objects before taking action. Many established approaches in robotics rely on mathematical models due to their analytical tractability. However, as robotic systems become more complex and are required to interact with physical environments, we encounter limitations in finding analytically tractable models. Thus, we must turn to new models that harness the computational power embedded in these systems.
To address the challenges of robot operation in physical environments, we propose the concept of building computational models using physics engines and designing feedback algorithms to autotune model parameters (mass, inertia, friction of objects) whenever the robot detects disparities between the simulation and its real-world experience. As part of our key applications, we plan to use this new model to train robotic manipulators for tasks in assembly lines and research laboratories that are labor-intensive and require dexterous skills.
Coral reefs, surrounded by vibrant marine life, constitute rich and diverse habitats. Given their ecological and economic significance, continuous monitoring of their key areas is paramount for marine biology research, economic development, and environmental protection. The extended survey and observation of vast marine environments are labor-intensive, necessitating technological advancements. While many efforts have been made in research and development to create autonomous robots capable of surveying and collecting data in remote areas inaccessible to human divers or requiring long-term and repeated monitoring, technical challenges remain. These challenges include implementing navigation strategies for individual underwater robots to operate in close proximity to marine life for extended periods while ensuring safety and non-interference with natural habitats.
Additionally, the severe signal attenuation underwater poses technical obstacles in information exchange and achieving a high degree of coordination among multiple robots tasked with surveying large-scale coral reef environments. The project explores learning-based planning and control approaches for individual robots to acquire safe navigation strategies and adaptively apply them in response to environmental conditions, such as light conditions and current speeds.
Furthermore, drawing from theoretical studies in multi-agent coordination, we aim to investigate how the robots can adopt optimal team strategies while working under the constraints of limited information exchange.
Past Research Projects
For further research activities see past research projects and list of publications.