Related papers: PhantomLiDAR: Cross-modality Signal Injection Atta…
The proliferation of electric vehicles in recent years has significantly expanded the charging infrastructure while introducing new security risks to both vehicles and chargers. In this paper, we investigate the security of major charging…
This paper presents a novel fusion technique for LiDAR Simultaneous Localization and Mapping (SLAM), aimed at improving localization and 3D mapping using LiDAR sensor. Our approach centers on the Inferred Attention Fusion (INAF) module,…
LiDAR model selection is a critical issue in roadside sensing systems, as it directly determines both perception capability and deployment cost. However, the lack of empirical benchmarks for comparing perception performance across different…
LiDAR-camera extrinsic calibration (LCEC) is crucial for data fusion in intelligent vehicles. Offline, target-based approaches have long been the preferred choice in this field. However, they often demonstrate poor adaptability to…
The LIght Detection And Ranging (LiDAR) sensor has become one of the most important perceptual devices due to its important role in simultaneous localization and mapping (SLAM). Existing SLAM methods are mainly developed for mechanical…
We address the problem of constructing false data injection (FDI) attacks that can bypass the bad data detector (BDD) of a power grid. The attacker is assumed to have access to only power flow measurement data traces (collected over a…
Physical side-channel attacks represent a great challenge for today's chip design. Although attacks on CMOS dynamic power represent a class of state-of-the-art attacks, many other effects potentially affect the security of CMOS chips…
Embodied AI systems, including AI-powered robots that autonomously interact with the physical world, stand to be significantly advanced by Large Language Models (LLMs), which enable robots to better understand complex language commands and…
The fiducial marker system for LiDAR is crucial for the robotic application but it is still rare to date. In this paper, an Intensity Image-based LiDAR Fiducial Marker (IILFM) system is developed. This system only requires an unstructured…
The integration of Large Language Models (LLMs) like GPT-4o into robotic systems represents a significant advancement in embodied artificial intelligence. These models can process multi-modal prompts, enabling them to generate more…
LiDAR sensors are widely used in autonomous vehicles to better perceive the environment. However, prior works have shown that LiDAR signals can be spoofed to hide real objects from 3D object detectors. This study explores the feasibility of…
A Cardiac Implantable Medical device (IMD) is a device, which is surgically implanted into a patient's body, and wirelessly configured using an external programmer by prescribing physicians and doctors. A set of lethal attacks targeting…
Sensor fusion has become a popular topic in robotics. However, conventional fusion methods encounter many difficulties, such as data representation differences, sensor variations, and extrinsic calibration. For example, the calibration…
Millimetre-wave observations represent an important tool for Cosmology studies. The Line Intensity Mapping (LIM) technique has been proposed to map in three dimensions the specific intensity due to line (e.g. [CII], CO) emission, for…
Lidar-based simultaneous localization and mapping (SLAM) approaches have obtained considerable success in autonomous robotic systems. This is in part owing to the high-accuracy of robust SLAM algorithms and the emergence of new and…
Localization can be achieved by different sensors and techniques such as a global positioning system (GPS), wifi, ultrasonic sensors, and cameras. In this paper, we focus on the laser-based localization method for unmanned aerial vehicle…
The rise of portable Lidar instruments, including their adoption in smartphones, opens the door to novel computational imaging techniques. Being an active sensing instrument, Lidar can provide complementary data to passive optical sensors,…
In this letter we investigate a tightly coupled Lidar-Inertia Odometry and Mapping (LIOM) scheme, with the capability to incorporate multiple lidars with complementary field of view (FOV). In essence, we devise a time-synchronized scheme to…
The fusion of sensor data from heterogeneous sensors is crucial for robust perception in various robotics applications that involve moving platforms, for instance, autonomous vehicle navigation. In particular, combining camera and lidar…
This paper proposes LONER, the first real-time LiDAR SLAM algorithm that uses a neural implicit scene representation. Existing implicit mapping methods for LiDAR show promising results in large-scale reconstruction, but either require…