The mission of our research group at CPSquare is centered around the development of theoretical and experimental methods for robotics, automation, and cyber-physical systems (CPS), including autonomous vehicles, unmanned aerial vehicles, and robot manipulators. We concentrate our efforts on three major research directions, as outlined below. By exploring these interdisciplinary areas, we strive to contribute to the advancement of robotics and its practical applications, ultimately enhancing automation, efficiency, and safety in various domains.

This research direction focuses on the development of motion planning and control algorithms that ensure safety and robustness in cyber-physical systems, particularly for multi-agent autonomous vehicles and drones. By incorporating advanced techniques from control theory, artificial intelligence, and machine learning, the goal is to create systems capable of operating in complex and uncertain environments while minimizing the risk of accidents or failures. The ultimate aim is to enable seamless and reliable operation of autonomous systems in diverse and dynamic scenarios, improving their overall performance and applicability in critical missions.

This research direction explores the use of visual servoing and motion planning techniques to enhance the capabilities of robotic manipulators in industrial settings and pick and place applications. The research combines the power of robotic vision techniques with traditional robotic motion planning methods to enable robots to perceive and interact with their environment more effectively. By developing advanced object recognition, tracking, and pose estimation algorithms, the goal is to enable robotic systems to autonomously perform tasks such as assembly, inspection, and packaging with improved accuracy and efficiency. This research has the potential to revolutionize the automation landscape in manufacturing and logistics, leading to increased productivity and reduced operational costs.

Agricultural Robotics is a research direction aimed at developing and deploying robotic systems to address various challenges in agriculture. By integrating advanced sensing, actuation, and autonomous decision-making capabilities, the goal is to create solutions that can optimize crop management, reduce labor requirements, and minimize environmental impact. Key areas of investigation include autonomous navigation for field robots, precision agriculture techniques for crop monitoring and treatment, and the development of specialized robotic systems for tasks such as planting, harvesting, and weed control. The ultimate aim is to enhance agricultural efficiency, sustainability, and overall productivity by leveraging robotics and automation technologies.

We are consistently seeking ambitious graduate and undergraduate students interested in cyber-physical systems and robotics. If you're motivated by addressing fundamental challenges for autonomous systems and are considering theoretical/experimental research collaborations at Cal Poly, feel free to contact sfarzan@calpoly.edu.