Workshop
International Conference on Image Processing and Robotics

Optimizing control and trajectory planning for large systems of unmanned aerial vehicles using swarm intelligence.

Kolitha Warnakulasooriya
PhD Researcher
School of Computing, University of South Alabama, United States

Autonomous precise control is a critical factor and a significant challenge for large UAV systems. Cooperative intelligence plays a vital role in ensuring smooth and fault-free mission completion. Nature offers remarkable insights through the swarming behavior of biological entities, demonstrating how to operate as a group to achieve specific objectives. Swarm intelligence has been developed for various applications, with high-order optimization being a particularly valuable aspect for optimizing multiple UAV systems. This session will delve into how swarming behavior, inspired by nature, provides substantial support for optimizing trajectories and enhancing control precision. We will cover a comprehensive introduction, explore the current state of trajectory optimization, and discuss the usefulness and limitations of swarm intelligence in the context of large-scale multiple UAV systems.

Computational Imaging Techniques for Quanta Image Sensors

Yoshihiro Maeda Associate Professor
Shibaura Institute of Technology, Tokyo, Japan

Quanta image sensors (QIS) are an emerging class of sensors capable of capturing individual photons with ultra-high temporal resolution. These sensors enable new applications in difficult imaging conditions, such as low-light scenes or fast motion.
Unlike conventional sensors, QIS outputs a sequence of binary images indicating whether a photon was incident at each pixel. While this mechanism offers high sensitivity, it also introduces unique challenges for image processing.
This session introduces our research on computational imaging techniques for QIS.
Topics include the challenges of processing binary images and the use of model-based and data-driven methods to reconstruct clear images.