13 accepted papers
In agriculture, understanding the distribution and relationship between different aspects of the environment is important for minimizing chemical use and reducing environmental impact. Traditionally, it is done by manually collecting samples on the field and then sending them to a laboratory for ana
Perception plays a crucial role in various robot applications. However existing well-annotated datasets are biased towards autonomous driving scenarios while unlabelled SLAM datasets are quickly over-fitted and often lack environment and domain variations. To expand the frontier of these fields we i…
In response to the evolving challenges posed by small unmanned aerial vehicles (UAVs), which possess the potential to transport harmful payloads or independently cause damage, we introduce MMAUD: a comprehensive Multi-Modal Anti-UAV Dataset. MMAUD addresses a critical gap in contemporary threat dete…
In this letter, we study the problem of estimating the unknown metric scale of an odometry system and the 3D location of an Ultra-wideband (UWB) anchor in the environment. Firstly, we present a theoretical analysis of the problem which includes the derivation of Fisher Information Matrix (FIM) and i
In multi-robot systems, two important research problems are relative localization between the robots and global localization of all robots in a common frame. Traditional methods rely on detecting inter and intra-robot loop closures, which can be restrictive operation-wise since the robot must form l
In recent years, thanks to the continuously reduced cost and weight of 3D lidar, the applications of this type of sensor in the community have become increasingly popular. Despite many progresses, estimation drift and tracking loss are still prevalent concerns associated with these systems. However,…
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 combine extracted features from separate lidars into a sing
In this work, we present a tightly-coupled fusion scheme of a monocular camera, a 6-DoF IMU, and a single unknown Ultra-wideband (UWB) anchor to achieve accurate and drift-reduced localization. Specifically, this letter focuses on incorporating the UWB sensor into an existing state-of-the-art visual
In this work, we propose a tightly-coupled odometry framework, which combines monocular visual feature observations with distance measurements provided by a single ultra-wideband (UWB) anchor with an initial guess for its location. Firstly, the scale factor and the anchor position in the vision fram…
In multi-robot systems, the capability of each robot to relatively localize its neighbors is a crucial requirement, which needs to be resolved as a prerequisite for almost any distributed scheme of operation. Notably, this problem proves to be quite challenging in GPS-denied environments. In this le
Though vision-based techniques have become quite popular for autonomous docking of Unmanned Aerial Vehicles (UAVs), due to limited field of view (FOV), the UAV must rely on other methods to detect and approach the target before vision can be used. In this paper we propose a method combining Ultra-wi…
In this paper we study the distance-based docking problem of unmanned aerial vehicles (UAVs) by using a single landmark placed at an arbitrarily unknown position. To solve the problem, we propose an integrated estimation-control scheme to simultaneously achieve the relative localization and navigati…