Navigation

This paper reviews the state of the arts of the application of deep learning for autonomous navigation.

This paper proposes three deep learning model for inertial attitude estimation.

Abstract This article discusses the importance of accurate and precise attitude determination in navigation for air and space vehicles. Various instruments and sensors have been developed over the last few decades to achieve this goal. However, the cost and complexity of these instruments can be prohibitive. To address this issue, Multi-Data Sensor Fusion (MSDF) techniques have been developed, which allow for the use of multiple sensors to sense a quantity from different perspectives or sense multiple quantities to reduce errors and uncertainties....

Abstract Despite recent advancments in Micro-Electro Mechanical Systems (MEMS) inertial and magnetic sensors, percices and accurate attitude estimation is a challenging task, especillay in the existance of magnetic distubances or high dynamic motions. This problem cannot be significantly tackled by conventional methods and clasical estimators. In this paper, an end-to-end deep learning framework is develped to estimate the attitude and heading using inertial and magentic sensors obtained from a low-cost IMU....

Abstract Introduction Achieving accurate and precise attitude determination or estimation is needed to perform successful navigation. Each flying vehicle either in air or space, needs to determine and control its attitude based on mission requirements. Vast variety of instruments/sensors and algorithm have been developed in the last decades; they are distinct by their cost and complexity. Use an accurate sensor will exponentially increase the cost which could exceed the budget. A solution for increase the accuracy with low cost is to use multi sensors (homogenous or heterogenous); multiple sensors could sense a quantity from different perspective or sense multi quantities to reduce the error and uncertainty....

Abstract Introduction Self-localization is one of the main challenges in the application of autonomous systems. These strategies can be divided into two major categories, GPS-based and Odometry. Odometry or position tracking is a form of navigation to detect the position and orientation of a robot by measuring the distance and angle of the robot’s movement using sensor data (e.g., inertial, visual, and radar). Position tracking is a fundamental task in autonomous navigation and it is a key component in many other applications, such as robotics, autonomous vehicles, and augmented reality....

Spacecraft Trajectory Optimization Introduction Spacecraft trajectory optimization plays a pivotal role in the realm of aerospace engineering, enabling the design of efficient and feasible paths for spacecraft to traverse between different points in space while considering a multitude of constraints and objectives. In this post we aimed to delve into advanced techniques and methodologies for spacecraft trajectory optimization. Space missions demand precise and optimal trajectory planning to achieve desired objectives, such as minimizing fuel consumption, reducing mission duration, reaching specific targets, or avoiding hazardous areas....