Visual navigation for autonomous, precise and safe landing on celestial bodies using unscented Kalman filtering

Ammann, Nikolaus; Andert, Franz

doi:10.1109/aero.2017.7943933

Cited by 12 publications

(8 citation statements)

References 20 publications

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“…The high payload capabilities allow the aircraft to carry multiple sensor systems, computational resources, and data links. This extensive range of avionic equipment plays an important role in improving the situational awareness of the aircraft [3] during the flight. It facilitates safe autonomous research missions which include flying in urban or maritime areas, alone or with other aircraft.…”

Section: Setupmentioning

confidence: 99%

RTLola Cleared for Take-Off: Monitoring Autonomous Aircraft

Baumeister

Finkbeiner

Schirmer

et al. 2020

Lecture Notes in Computer Science

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The autonomous control of unmanned aircraft is a highly safety-critical domain with great economic potential in a wide range of application areas, including logistics, agriculture, civil engineering, and disaster recovery. We report on the development of a dynamic monitoring framework for the DLR ARTIS (Autonomous Rotorcraft Testbed for Intelligent Systems) family of unmanned aircraft based on the formal specification language RTLola. RTLola is a stream-based specification language for real-time properties. An RTLola specification of hazardous situations and system failures is statically analyzed in terms of consistency and resource usage and then automatically translated into an FPGA-based monitor. Our approach leads to highly efficient, parallelized monitors with formal guarantees on the noninterference of the monitor with the normal operation of the autonomous system.

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Section: Setupmentioning

confidence: 99%

RTLola Cleared for Take-Off: Monitoring Autonomous Aircraft

Baumeister

Finkbeiner

Schirmer

et al. 2020

Lecture Notes in Computer Science

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show abstract

“…This module uses the output of the Feature Tracker, the Crater Navigation, the Shadow Matching and the 3D Matching along with the raw IMU, Altimeter and Star Tracker measurements to estimate the true navigation solution. The Navigation Filter is based on high-rate strap-down computation and a low-rate error-state Unscented Kalman Filter (UKF) [1]. The strap-down algorithm uses the IMU measurements to propagate the total navigation solution forward in time for each measurement.…”

Section: Navigation Filtermentioning

confidence: 99%

ATON (Autonomous Terrain-based Optical Navigation) for exploration missions: recent flight test results

et al. 2018

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Since 2010 the German Aerospace Center (DLR) is working on the project ATON (Autonomous Terrain-based Optical Navigation). Its objective is the development of technologies which allow autonomous navigation of spacecraft in orbit around and during landing on celestial bodies like the Moon, planets, asteroids and comets. The project developed different image processing techniques and optical navigation methods as well as sensor data fusion. The setup-which is applicable to many exploration missions-consists of an inertial measurement unit (IMU), a laser altimeter, a star tracker and one or multiple navigation cameras. In the past years, several milestones have been achieved. It started with the setup of a simulation environment including the detailed simulation of camera images. This was continued by hardware-in-the-loop tests in the Testbed for Robotic Optical Navigation where images were generated by real cameras in a simulated downscaled lunar landing scene. Data was recorded

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“…• Navigation Filter: The Navigation Filter module combines and fuses the raw measurements from the sensors (IMU, altimeter, and star tracker), and the preprocessed data from the described modules to a navigation solution. It is based on high-rate strap-down computation and a low-rate error-state Unscented Kalman Filter (UKF) [13], [14]. The strap-down algorithm uses the IMU measurements to propagate the total navigation solution forward in time for each measurement.…”

Section: Dlr's Project Atonmentioning

confidence: 99%

Using an UAV for testing an autonomous terrain-based optical navigation system for lunar landing

Ammann

Theil

2018

2018 IEEE Aerospace Conference

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This paper presents the application of a rotary wing Unmanned Aerial Vehicle (UAV) as a testbed for the optical navigation system developed in the project "Autonomous Terrainbased Optical Navigation" (ATON) of the German Aerospace Center (DLR). Since using optical sensor data in navigation systems for exploration missions is a promising technology, many projects have focused on the development of such navigation systems. To allow autonomous operation of these developed navigation technologies in the targeted environment extensive testing is necessary for achieving an appropriate grade of reliability. A review of the current approaches for true-scale testing of optical navigation systems for lunar or planetary landing missions is conducted, and the proposed testing methodology is motivated. The paper describes the development steps necessary to conduct closed-loop real-time flight tests using a rotary wing UAV. This includes the sensor configuration, preparation of the flight test area and ground truth generation. Finally, the resulting navigation performance of the ATON navigation system in the closed-loop real-time flight tests is presented.

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Visual navigation for autonomous, precise and safe landing on celestial bodies using unscented Kalman filtering

Cited by 12 publications

References 20 publications

RTLola Cleared for Take-Off: Monitoring Autonomous Aircraft

RTLola Cleared for Take-Off: Monitoring Autonomous Aircraft

ATON (Autonomous Terrain-based Optical Navigation) for exploration missions: recent flight test results

Using an UAV for testing an autonomous terrain-based optical navigation system for lunar landing

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