Planning an autonomous vehicle's (AV) path in a space shared with pedestrians requires
reasoning about pedestrians' future trajectories. A practical pedestrian trajectory prediction …

The electrification of vehicle helps to improve its operation efficiency and safety. Due to fast
development of network, sensors, as well as computing technology, it becomes realizable to …

Rigorous and comprehensive testing plays a key role in training self-driving cars to handle a
variety of situations that they are expected to see on public roads. The physical testing on …

This paper presents a latent space reinforcement learning method for interpretable decision-
making of autonomous vehicles at highway on-ramps. This method is based on the latent …

As an important component of autonomous systems, autonomous car perception has had a
big leap with recent advances in parallel computing architectures. With the use of tiny but full …

Light detection and ranging (LiDAR) sensor has become one of the primary sensors in
robotics and autonomous system for high-accuracy situational awareness. In recent years …

Over the last decade, robotic perception algorithms have significantly benefited from the
rapid advances in deep learning (DL). Indeed, a significant amount of the autonomy stack of …

Using different sensors in an autonomous vehicle (AV) can provide multiple constraints to
optimize AV location estimation. In this paper, we present a low-cost GPS-assisted LiDAR …

As an unmanned aerial vehicle (UAV) navigates autonomously, there are unanticipated
occasions, eg, loss of data provided by the global navigation satellite system, where its …

Unmanned aerial vehicles (UAVs) are at the forefront of this century's technological shift,
becoming ubiquitous in research and market areas. However, as a UAV navigates …