Vision-Based Navigation for the NASA Mars Helicopter

  title={Vision-Based Navigation for the NASA Mars Helicopter},
  author={David S. Bayard and Dylan T. Conway and Roland Brockers and Jeff Delaune and Larry H. Matthies and H{\aa}vard Fj{\ae}r Grip and Gene B. Merewether and Travis Brown and A.M. San Martin},
  journal={AIAA Scitech 2019 Forum},
Range-Visual-Inertial Odometry: Scale Observability Without Excitation
A novel range measurement update model based on using facet constraints is introduced that enables simple and robust autonomous operations over arbitrary terrain, and is released as an open source framework, called xVIO.
A Review of Current Approaches for UAV Autonomous Mission Planning for Mars Biosignatures Detection
Recognising the importance of astrobiology in Mars exploration, progress is highlighted in the area of autonomous biosignature detection capabilities trialed on Earth, and the objectives and challenges in relation to future missions to Mars are discussed.
xVIO: A Range-Visual-Inertial Odometry Framework
This report is a complete technical description of xVIO, including an overview of the system architecture, the implementation of the navigation filter, along with the derivations of the Jacobian matrices which are not already published in the literature.
Inertia Measurement Unit-Based Displacement Estimation via Velocity Drift Compensation Using Ordinary Least Squares Method
In this study, we propose a methodology to retrieve displacement estimates from acceleration data by employing a drift compensation algorithm. The sensing device used in this study is a micro
Exploring Event Camera-based Odometry for Planetary Robots
EKLT-VIO is introduced, which addresses both limitations by combining a state-of-the-art event-based frontend with a filter-based backend that makes it both accurate and robust to uncertainties, outperforming event- and frame-based VIO algorithms on challenging benchmarks by 32%.
Multi-Resolution Elevation Mapping and Safe Landing Site Detection with Applications to Planetary Rotorcraft
A resource-efficient approach to provide an autonomous UAV with an on-board perception method to detect safe, hazard-free landing sites during flights over complex 3D terrain and the performance of the mapping and landing site detection modules is analyzed.
Towards Robust Monocular Visual Odometry for Flying Robots on Planetary Missions
An advanced robust monocular odometry algorithm that uses efficient optical flow tracking to obtain feature correspondences between images and a refined keyframe selection criterion and a novel approach to estimate the current risk of scale drift based on a principal component analysis of the relative translation information matrix is presented.
Dare Mighty Things: Fly on Mars [Young Professionals]
  • N. Chahat
  • Business
    IEEE Antennas and Propagation Magazine
  • 2021
In this issue of IEEE Antennas and Propagation Magazine, we are excited to have a very interesting contribution to the “Young Professionals” column from Dr. Nacer Chahat of NASA’s Jet Propulsion


Reduced-Order Kalman Filtering with Relative Measurements
In this paper, the symbol zk is used to denote a relative measurement, shown in Eq. (1), and yk is used to denote a conventional measurement, shown in Eq. (2). As an example, let x 2 R denote the
Flight Control System for NASA's Mars Helicopter
A high-level overview of the flight control system for the Mars Helicopter, including the Guidance, Navigation, and Control subsystems, and the implementation of these on the flight avionics hardware is presented.
On-board vision-based spacecraft estimation algorithm for small body exploration
A methodology is summarized for designing on-board state estimators in support of spacecraft exploration of small bodies such as asteroids and comets. This paper focuses on an estimation algorithm
Feature and pose constrained visual Aided Inertial Navigation for computationally constrained aerial vehicles
A Feature and Pose Constrained Extended Kalman Filter (FPC-EKF) is developed for highly dynamic computationally constrained micro aerial vehicles that efficiently incorporates measurements from hundreds of opportunistic visual features to constrain the motion estimate, while allowing navigating and sustained tracking with respect to a few persistent features.
Detecting and dealing with hovering maneuvers in vision-aided inertial navigation systems
This paper examines the VINS system's unobservable directions for two common hovering conditions and proposes a robust motion-classification algorithm, based on both visual and inertial measurements, which is validated experimentally on a quadrotor with rapid transitions between hovering and forward motions.
Stochastic cloning: a generalized framework for processing relative state measurements
  • S. Roumeliotis, J. Burdick
  • Computer Science
    Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292)
  • 2002
A generalized framework, termed "stochastic cloning," for processing relative state measurements within a Kalman filter estimator, aimed at fusing displacement measurements with position estimates for mobile robot localization is introduced.
Machine Learning for High-Speed Corner Detection
It is shown that machine learning can be used to derive a feature detector which can fully process live PAL video using less than 7% of the available processing time.
MonoSLAM: Real-Time Single Camera SLAM
The first successful application of the SLAM methodology from mobile robotics to the "pure vision" domain of a single uncontrolled camera, achieving real time but drift-free performance inaccessible to structure from motion approaches is presented.
A Multi-State Constraint Kalman Filter for Vision-aided Inertial Navigation
The primary contribution of this work is the derivation of a measurement model that is able to express the geometric constraints that arise when a static feature is observed from multiple camera poses, and is optimal, up to linearization errors.