Related papers: RINS-W: Robust Inertial Navigation System on Wheel…
Reliable vehicle navigation in urban environments remains a challenging problem due to frequent satellite signal blockages caused by tall buildings and complex infrastructure. While fusing inertial reading with satellite positioning in an…
In motion tracking of connected multi-body systems Inertial Measurement Units (IMUs) are used in a wide variety of applications, since they provide a low-cost easy-to-use method for orientation estimation. However, in indoor environments or…
Velocity estimation plays a central role in driverless vehicles, but standard and affordable methods struggle to cope with extreme scenarios like aggressive maneuvers due to the presence of high sideslip. To solve this, autonomous race cars…
Robotic underwater systems, e.g., Autonomous Underwater Vehicles (AUVs) and Remotely Operated Vehicles (ROVs), are promising tools for collecting biogeochemical data at the ice-water interface for scientific advancements. However, state…
In recent years, thanks to the continuously reduced cost and weight of 3D Lidar, the applications of this type of sensor in robotics community have become increasingly popular. Despite many progresses, estimation drift and tracking loss are…
In this paper, we propose an interoceptive-only odometry system for ground robots with neural network processing and soft constraints based on the assumption of a globally continuous ground manifold. Exteroceptive sensors such as cameras,…
This paper presents a convolutional neural network based foot motion tracking with only six-axis Inertial-Measurement-Unit (IMU) sensor data. The presented approach can adapt to various walking conditions by adopting differential and window…
Accurate and reliable estimation of biases of low-cost Inertial Measurement Units (IMU) is a key factor to maintain the resilience of Visual-Inertial Odometry (VIO), particularly when visual tracking fails in challenging areas. In such…
Pedestrian tracking has long been considered an important problem, especially in security applications. Previously,many approaches have been proposed with various types of sensors. One popular method is Pedestrian Dead Reckoning(PDR) [1]…
This paper presents a task-oriented computational framework to enhance Visual-Inertial Navigation (VIN) in robots, addressing challenges such as limited time and energy resources. The framework strategically selects visual features using a…
Applications of inertial measurement units are extremely diverse, and are expected to see a further increase in number due to current trends in robotics as well as recent advances in Micro Electromechanical sensors (MEMS). The traditional…
The common approach to inertial sensor calibration for navigation purposes has been to model the stochastic error signals of individual sensors independently, whether as components of a single inertial measurement unit (IMU) in different…
Mobile robots are used in industrial, leisure, and military applications. In some situations, a robot navigation solution relies only on inertial sensors and as a consequence, the navigation solution drifts in time. In this paper, we…
We study a Visual-Inertial Navigation (VIN) problem in which a robot needs to estimate its state using an on-board camera and an inertial sensor, without any prior knowledge of the external environment. We consider the case in which the…
Vision-based odometry has been widely adopted in autonomous driving owing to its low cost and lightweight setup; however, its performance often degrades in complex outdoor urban environments. To address these challenges, we propose…
Inertial navigation computation is to acquire the attitude, velocity and position information of a moving body by integrating inertial measurements from gyroscopes and accelerometers. Over half a century has witnessed great efforts in…
This work proposes algorithms for reconstruction of closed-loop pedestrian trajectories based on two foot-mounted inertial measurement units (IMU). The first proposed algorithm allows calculation of a trajectory using measurements from only…
Autonomous underwater vehicles (AUVs) are sophisticated robotic platforms crucial for a wide range of applications. The accuracy of AUV navigation systems is critical to their success. Inertial sensors and Doppler velocity logs (DVL) fusion…
This paper reports on developing a real-time invariant proprioceptive robot state estimation framework called DRIFT. A didactic introduction to invariant Kalman filtering is provided to make this cutting-edge symmetry-preserving approach…
Autonomous navigation for legged robots in complex and dynamic environments relies on robust simultaneous localization and mapping (SLAM) systems to accurately map surroundings and localize the robot, ensuring safe and efficient operation.…