Researchers from Koç University and international collaborators have developed a new algorithm that enables faster and more ...

Researchers have proposed a novel active equalization scheme for lithium-ion batteries that uses path planning to address ...

This important study advances our understanding of the neural substrate of planning trajectories towards a goal by using recurrent neural networks. The manuscript provides solid evidence for most of ...

Abstract: Path planning is a crucial component for robotics and autonomous systems, which facilitate navigation through dynamic and uncertain environments while avoiding obstacles. This review paper ...

Robotic systems are transforming image-guided interventions by enhancing accuracy and minimizing radiation exposure. A significant challenge in robotic assistance lies in surgical path planning, which ...

In a study published in Robot Learning journal, researchers propose a new learning-based path planning framework that allows mobile robots to navigate safely and efficiently using a Transformer model.

The path planning capability of autonomous robots in complex environments is crucial for their widespread application in the real world. However, long-term decision-making and sparse reward signals ...

"Breaking the Sorting Barrier for Directed Single-Source Shortest Paths" by Ran Duan, Jiayi Mao, Xiao Mao, Xinkai Shu, and Longhui Yin (2025) Use the road_network_benchmark example to evaluate the ...

Shortest path algorithms sit at the heart of modern graph theory and many of the systems that move people, data, and goods around the world. After nearly seventy years of relying on the same classic ...

Imagine a robot that doesn’t just follow commands but actually plans its actions, adjusts its movements on the go, and learns from feedback—much like a human would. This may sound like a far-fetched ...