Helicopter Flight Testing of a Real-Time Hazard Detection System for Safe Lunar Landing

Carson, John M.; Trawny, Nikolas; Huertas, A.; Luna, Michael E.; Roback, Vincent E.; Johnson, Andrew; Martin, K. E.

doi:10.2514/6.2013-5313

Cited by 9 publications

(1 citation statement)

References 13 publications

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“…Nowadays, Several trials have been carried out during the course of NASA's ALHAT project to validate the hazard detection method using LiDAR sensor on-board a helicopter (Carson et al, 2013a;Carson et al, 2015;Carson et al, 2013b;Epp et al, 2014;Epp and Smith, 2007;Trawny et al, 2015;Villalpando et al, 2013). Likewise, NASA proposed to develop the 3D Imaging Flash LiDAR system to hazard detection for future planetary landing missions (Amzajerdian et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Simulation Experiment on Landing Site Selection Using a Simple Geometric Approach

Zhao

Tong

Xie

et al. 2017

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Safe landing is an important part of the planetary exploration mission. Even fine scale terrain hazards (such as rocks, small craters, steep slopes, which would not be accurately detected from orbital reconnaissance) could also pose a serious risk on planetary lander or rover and scientific instruments on-board it. In this paper, a simple geometric approach on planetary landing hazard detection and safe landing site selection is proposed. In order to achieve full implementation of this algorithm, two easy-to-compute metrics are presented for extracting the terrain slope and roughness information. Unlike conventional methods which must do the robust plane fitting and elevation interpolation for DEM generation, in this work, hazards is identified through the processing directly on LiDAR point cloud. For safe landing site selection, a Generalized Voronoi Diagram is constructed. Based on the idea of maximum empty circle, the safest landing site can be determined. In this algorithm, hazards are treated as general polygons, without special simplification (e.g. regarding hazards as discrete circles or ellipses). So using the aforementioned method to process hazards is more conforming to the real planetary exploration scenario. For validating the approach mentioned above, a simulated planetary terrain model was constructed using volcanic ash with rocks in indoor environment. A commercial laser scanner mounted on a rail was used to scan the terrain surface at different hanging positions. The results demonstrate that fairly hazard detection capability and reasonable site selection was obtained compared with conventional method, yet less computational time and less memory usage was consumed. Hence, it is a feasible candidate approach for future precision landing selection on planetary surface.

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Section: Introductionmentioning

confidence: 99%

Simulation Experiment on Landing Site Selection Using a Simple Geometric Approach

Zhao

Tong

Xie

et al. 2017

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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In-flight experience of the Mars Science Laboratory Guidance, Navigation, and Control system for Entry, Descent, and Landing

et al. 2015

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Landing (EDL) system: the large reduction in the size of the Landing Ellipse and the large increase in the Landed Mass as compared to previous missions [1,2].The reduction in the size of the Landing Ellipse was dictated by the desire to give scientists more choices when selecting sites of great scientific value and still safe for landing the Curiosity rover. Scientists made maximum use of this new capability when they selected Gale Crater as the landing site, boldly placing the ellipse at the crater's floor between the dangers of its rim at one side and Mt Sharp (a 5.5 km high mountain in its center) at the other (Fig. 1). Figure 2 illustrates the reduction of the landing ellipses since Viking against a picture of Gale Crater. Only MSL landing ellipse can fit in the tight space within the crater.The increase in the landed mass capability of MSL EDL was dictated by the mass of the Curiosity rover, which itself was driven by the size and complexity of its scientific instruments and the need for improved mobility. Figure 3 compares the size of Curiosity against the previous Mars rovers.To meet the first challenge, Landing Ellipse reduction, MSL employed the first use at Mars of Entry Guidance. This technique, which was used successfully by Gemini and Apollo to guide the capsules precisely and safely through the Earth's atmosphere to land closely to recovery assets, requires a lifting capsule (Fig. 4), on-board guidance, navigation and control software, and an RCS propulsion system to stabilize and control the roll of the capsule to point its Lift vector as commanded by the on-board guidance function.To meet the challenge of placing, a 1 ton class rover with the size of a small car on the surface of Mars, MSL had to invent a totally new landing architecture: the SkyCrane (Fig. 5). This architecture solved the rover-egress problem (i.e., how to lower the rover from the top deck of a Viking style legged lander) by placing the rover on the surface of Abstract The Mars Science Laboratory (MSL) project successfully landed the rover Curiosity in Gale crater in August 5, 2012, thus demonstrating and validating a series of technical innovations and advances which resulted in a quantum leap in Entry, Descent, and Landing (EDL) performance relative to previous missions. These included the first use at Mars of Entry Guidance to reduce the size of the landing ellipse and the first use of the SkyCrane landing architecture to enable the placement of a 1 ton class rover on the surface of the red planet. Both of these advances required innovations in the design, analysis and testing of the Guidance, Navigation, and Control system. This paper will start with a high-level description of the MSL EDL/GN&C system design and performance requirements, followed by a brief discussion of the risks and uncertainties as they were understood prior to landing, and the actual in-flight GN&C performance as reconstructed from telemetry. Finally, this paper will address areas of improvements for future Mars EDL missions.

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A multilayer perceptron hazard detector for vision-based autonomous planetary landing

Lunghi

Ciarambino

Lavagna

2016

Advances in Space Research

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A hazard detection and target selection algorithm for autonomous spacecraft planetary landing, based on Artificial Neural Networks, is presented. From a single image of the landing area, acquired by a VIS camera during the descent, the system computes a hazard map, exploited to select the best target, in terms of safety, guidance constraints, and scientific interest. ANNs generalization properties allow the system to correctly operate also in conditions not explicitly considered during calibration. The net architecture design, training, verification and results are critically presented. Performances are assessed in terms of recognition accuracy and selected target safety. Results for a lunar landing scenario are discussed to highlight the effectiveness of the system

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Helicopter Flight Testing of a Real-Time Hazard Detection System for Safe Lunar Landing

Cited by 9 publications

References 13 publications

Simulation Experiment on Landing Site Selection Using a Simple Geometric Approach

Simulation Experiment on Landing Site Selection Using a Simple Geometric Approach

In-flight experience of the Mars Science Laboratory Guidance, Navigation, and Control system for Entry, Descent, and Landing

A multilayer perceptron hazard detector for vision-based autonomous planetary landing

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