Related papers: Mobile Robot Localization via Indoor Positioning S…
Odometry on aerial robots has to be of low latency and high robustness whilst also respecting the Size, Weight, Area and Power (SWAP) constraints as demanded by the size of the robot. A combination of visual sensors coupled with Inertial…
Accurate pose and velocity estimation is essential for effective spatial task planning in robotic manipulators. While centralized sensor fusion has traditionally been used to improve pose estimation accuracy, this paper presents a novel…
Kalman filter-based algorithms are fundamental for mobile robots, as they provide a computationally efficient solution to the challenging problem of state estimation. However, they rely on two main assumptions that are difficult to satisfy…
Robust and versatile localization techniques are key to the success of the next industrial revolution. Yet, it is uncertain which combination of sensors will be the most robust and valuable. Thus, we present a versatile and reproducible…
Visual servoing is fundamental to robotic applications, enabling precise positioning and control. However, applying it to textureless objects remains a challenge due to the absence of reliable visual features. Moreover, adverse visual…
Visual localization is a fundamental task that regresses the 6 Degree Of Freedom (6DoF) poses with image features in order to serve the high precision localization requests in many robotics applications. Degenerate conditions like motion…
We propose a distributed cooperative positioning algorithm using the extended Kalman filter (EKF) based spatio-temporal data fusion (STDF) for a wireless network composed of sparsely distributed high-mobility nodes. Our algorithm first…
Infrastructure-based sensing and real-time trajectory generation show promise for improving safety in high-risk roadway segments such as work zones, yet practical deployments are hindered by perspective distortion, complex geometry,…
This paper presents the use of multi-sensor measurement system to guide autonomous mobile robot in the house. The system allows the 3D image acquisition to global mapping, and algorithms to reduce the dimensionality of images to 2D global…
Extended Kalman filter (EKF) does not guarantee consistent mean and covariance under linearization, even though it is the main framework for robotic localization. While Lie group improves the modeling of the state space in localization, the…
Precise positioning and navigation information has been increasingly important with the development of the consumer electronics market. Due to some deficits of Global Navigation Satellite System (GNSS), such as susceptible to interferences,…
Reliable and real-time 3D reconstruction and localization functionality is a crucial prerequisite for the navigation of actively controlled capsule endoscopic robots as an emerging, minimally invasive diagnostic and therapeutic technology…
Indoor localization and Location Based Services (LBS) can greatly benefit from the widescale proliferation of communication devices. The basic requirements of a system that can provide the aforementioned services are energy efficiency,…
Indoor position technology has become one of the research highlights in the Internet of Things (IoT), but there is still a lack of universal, low-cost, and high-precision solutions. This paper conducts research on indoor position technology…
Navigation plays a vital role in the ability of autonomous surface and underwater platforms to complete their tasks. Most navigation systems apply a fusion between inertial sensors and other external sensors, such as global navigation…
Accurate time synchronization between heterogeneous sensors is crucial for ensuring robust state estimation in multi-sensor fusion systems. Sensor delays often cause discrepancies between the actual time when the event was captured and the…
Finding the position of the user is an important processing step for augmented reality (AR) applications. This paper investigates the use of different motion models in order to choose the most suitable one, and eventually reduce the Kalman…
Drift-free localization is essential for autonomous vehicles. In this paper, we address the problem by proposing a filter-based framework, which integrates the visual-inertial odometry and the measurements of the features in the pre-built…
Relative localization between autonomous robots without infrastructure is crucial to achieve their navigation, path planning, and formation in many applications, such as emergency response, where acquiring a prior knowledge of the…
In robotic navigation, maintaining precise pose estimation and navigation in complex and dynamic environments is crucial. However, environmental challenges such as smoke, tunnels, and adverse weather can significantly degrade the…