Advancements in Autonomous Systems and State Estimation

The field of autonomous systems and state estimation is experiencing significant developments, with a focus on safe planning and control in unknown environments. Researchers are exploring innovative approaches to guarantee safety and satisfy budget constraints, such as online methods and sampling-based techniques. Additionally, there is a growing interest in geometric approaches for pose and velocity estimation, as well as nonlinear observer design for simultaneous localization and mapping. These advancements have the potential to improve the performance and robustness of autonomous systems in various applications. Noteworthy papers in this area include:

  • A Geometric Approach For Pose and Velocity Estimation Using IMU and Inertial/Body-Frame Measurements, which proposes a geometric framework for state estimation.
  • Nonlinear Observer Design for Landmark-Inertial Simultaneous Localization and Mapping, which introduces a new matrix Lie group for SLAM applications.

Sources

Autonomy Architectures for Safe Planning in Unknown Environments Under Budget Constraints

A Geometric Approach For Pose and Velocity Estimation Using IMU and Inertial/Body-Frame Measurements

Nonlinear Observer Design for Landmark-Inertial Simultaneous Localization and Mapping

Prescribed-Time Boresight Control of Spacecraft Under Pointing Constraints

Covariance-Intersection-based Distributed Kalman Filtering: Stability Problems Revisited

Built with on top of