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This paper introduces AUTOBargeSim, a simulation toolbox for autonomous inland vessel guidance and control system design. AUTOBargeSim is developed using MATLAB and provides an easy-to-use introduction to various aspects of autonomous…
Quadruped robots are currently a widespread platform for robotics research, thanks to powerful Reinforcement Learning controllers and the availability of cheap and robust commercial platforms. However, to broaden the adoption of the…
Conventional ultrasonic inspection systems rely on phased arrays and high-performance computing hardware, making them costly, bulky, and unsuitable for portable or embedded use. In this work, we present nRTIS (nano Real-Time 3D Imaging…
Despite advancements in SLAM technologies, robust operation under challenging conditions such as low-texture, motion-blur, or challenging lighting remains an open challenge. Such conditions are common in applications such as assistive…
This paper proposes a photorealistic real-time dense 3D mapping system that utilizes a learning-based image enhancement method and mesh-based map representation. Due to the characteristics of the underwater environment, where problems such…
This technical report presents the construction and analysis of polynomial navigation functions for motion planning in 3-D workspaces populated by spherical and cylindrical obstacles. The workspace is modeled as a bounded spherical region,…
Bioinspired polarized skylight navigation system (PSNS) is a new navigation method, which imitates insects using polarized skylight for navigation. However, the latest research shows that the current PSNS is difficult to obtain the…
LiDAR sensors are widely used in autonomous driving due to the reliable 3D spatial information. However, the data of LiDAR is sparse and the frequency of LiDAR is lower than that of cameras. To generate denser point clouds spatially and…
Multimodal sensor fusion methods for 3D object detection have been revolutionizing the autonomous driving research field. Nevertheless, most of these methods heavily rely on dense LiDAR data and accurately calibrated sensors which is often…
The Simultaneous Localization And Mapping (SLAM) problem has been well studied in the robotics community, especially using mono, stereo cameras or depth sensors. 3D depth sensors, such as Velodyne LiDAR, have proved in the last 10 years to…
Radar odometry estimation has emerged as a critical technique in the field of autonomous navigation, providing robust and reliable motion estimation under various environmental conditions. Despite its potential, the complex nature of radar…
This article describes a guidance system of the autonomous underwater vehicle "DeepC" [1] in Special situations. A special situation occurs when one or more objects interfere with the planned route of a mission. The possible reactions are…
While effective navigation in large, crowded environments is essential for an autonomous robot, preliminary testing of algorithms to support it requires simulation across a broad range of crowd scenarios. Most available simulation tools…
This research addresses the challenge of estimating bathymetry from imaging sonars where the state-of-the-art works have primarily relied on either supervised learning with ground-truth labels or surface rendering based on the Lambertian…
Recently, the navigation of mobile robots in unknown environments has become a particularly significant research topic. Previous studies have primarily employed real-time environmental mapping using cameras and LiDAR, along with…
Miniaturization of cameras and LiDAR sensors has enabled the development of wearable 3D mapping systems for emergency responders. These systems have the potential to revolutionize response capabilities by providing real-time, high-fidelity…
Accurate perception of dynamic obstacles is essential for autonomous robot navigation in indoor environments. Although sophisticated 3D object detection and tracking methods have been investigated and developed thoroughly in the fields of…
Sim-to-real gap has long posed a significant challenge for robot learning in simulation, preventing the deployment of learned models in the real world. Previous work has primarily focused on domain randomization and system identification to…
Foresighted robot navigation in dynamic indoor environments with cost-efficient hardware necessitates the use of a lightweight yet dependable controller. So inferring the scene dynamics from sensor readings without explicit object tracking…
This paper introduces a statistical model and corresponding sequential Bayesian estimation method for terrain-based navigation using side-scan sonar (SSS) data. The presented approach relies on slant range measurements extracted from the…