A hybrid FPGA/Tilera compute element for autonomous hazard detection and navigation

Villalpando, Carlos Y.; Werner, Robert A.; Carson, John M.; Khanoyan, Garen; Stern, Ryan; Trawny, Nikolas

doi:10.1109/aero.2013.6496977

Cited by 17 publications

(8 citation statements)

References 11 publications

(8 reference statements)

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“…It is clear that, given the low amount of resources required by SA-FEMIP, fault tolerance techniques can be freely implemented within the selected device. Moreover, even after the implementation of fault tolerance techniques, space is also available to integrate, in the same device, additional FPGA-based IP-cores useful to accelerate other computationally intensive tasks performed during the descending phase (e.g., Hazard map computation [39]). This is very important considering the limited resources available in space applications.…”

Section: Resultsmentioning

confidence: 99%

SA-FEMIP: A Self-Adaptive Features Extractor and Matcher IP-Core Based on Partially Reconfigurable FPGAs for Space Applications

Carlo

Gambardella

Prinetto

et al. 2015

IEEE Trans. VLSI Syst.

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Video-based navigation (VBN) is increasingly used in space applications to enable autonomous entry, descent, and landing of aircrafts. VBN algorithms require real-time performances and high computational capabilities, especially to perform features extraction and matching (FEM). In this context, field-programmable gate arrays (FPGAs) can be employed as efficient hardware accelerators. This paper proposes an improved FPGA-based FEM module. Online self-adaptation of the parameters of both the image noise filter and the features extraction algorithm is adopted to improve the algorithm robustness. Experimental results demonstrate the effectiveness of the proposed self-adaptive module. It introduces a marginal resource overhead and no timing performance degradation when compared with the reference state-of-the-art architecture.Index Terms-Field-programmable gate array (FPGA), hardware acceleration, image processing, space applications, video-based navigation (VBN). 1063-8210

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Section: Resultsmentioning

confidence: 99%

SA-FEMIP: A Self-Adaptive Features Extractor and Matcher IP-Core Based on Partially Reconfigurable FPGAs for Space Applications

Carlo

Gambardella

Prinetto

et al. 2015

IEEE Trans. VLSI Syst.

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“…The HDS CE combines a Xilinx FPGA (surrogate for the path-to-flight Virtex-5 FPGA) and a multicore Tilera Tile-64 multicore processor (chosen for its common architecture with the Maestro processor developed under the Opera program 8 ), linked through a high-speed, 10 Gb/s XAUI connection. 9 The FPGA provides a precise hardware-based time stamp for all sensor data, and a time synchronization mechanism between the HDS and HV via an analog PPS pulse. The CE contains an optional data logger and console system (DLC).…”

Section: Hazard Detection System Architecturementioning

confidence: 99%

Flight testing a Real-Time Hazard Detection System for Safe Lunar Landing on the Rocket-Powered Morpheus Vehicle

Trawny

Huertas

Luna

et al. 2015

AIAA Guidance, Navigation, and Control Conference

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The Hazard Detection System (HDS) is a component of the ALHAT (Autonomous Landing and Hazard Avoidance Technology) sensor suite, which together provide a lander Guidance, Navigation and Control (GN&C) system with the relevant measurements necessary to enable safe precision landing under any lighting conditions. The HDS consists of a stand-alone compute element (CE), an Inertial Measurement Unit (IMU), and a gimbaled flash LIDAR sensor that are used, in real-time, to generate a Digital Elevation Map (DEM) of the landing terrain, detect candidate safe landing sites for the vehicle through Hazard Detection (HD), and generate hazard-relative navigation (HRN) measurements used for safe precision landing. Following an extensive ground and helicopter test campaign, ALHAT was integrated onto the Morpheus rocket-powered terrestrial test vehicle in March 2014. Morpheus and ALHAT then performed five successful free flights at the simulated lunar hazard field constructed at the Shuttle Landing Facility (SLF) at Kennedy Space Center, for the first time testing the full system on a lunar-like approach geometry in a relevant dynamic environment. During these flights, the HDS successfully generated DEMs, correctly identified safe landing sites and provided HRN measurements to the vehicle, marking the first autonomous landing of a NASA rocket-powered vehicle in hazardous terrain. This paper provides a brief overview of the HDS architecture and describes its in-flight performance.

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“…18 The HDS uses a flash lidar built by LaRC that is a compact, real-time, aircooled, 20 Hz TOF sensor system based on 3-D imaging camera technology developed by Advanced Scientific Concepts (ASC). 19 The LaRC lidar integrates a 1.064 μm class IV laser, 1 • field of view (FOV) f/7.3 receiver optics, 1 • divergence transmitter optics, and a 128 pixel × 128 pixel focal plane array (FPA) which resides in the ASC camera.…”

Section: Alhat Sensors and Vehicle Integrationmentioning

confidence: 99%

Flight Testing ALHAT Precision Landing Technologies Integrated Onboard the Morpheus Rocket Vehicle

Carson

Robertson

Trawny

et al. 2015

AIAA SPACE 2015 Conference and Exposition

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A suite of prototype sensors, software, and avionics developed within the NASA Autonomous precision Landing and Hazard Avoidance Technology (ALHAT) project were terrestrially demonstrated onboard the NASA Morpheus rocket-propelled Vertical Testbed (VTB) in 2014. The sensors included a lidar-based Hazard Detection System (HDS), a Navigation Doppler Lidar (NDL) velocimeter, and a long-range Laser Altimeter (LAlt) that enable autonomous and safe precision landing of robotic or human vehicles on solid solar system bodies under varying terrain lighting conditions. The flight test campaign with the Morpheus VTB involved a detailed integration and functional verification process, followed by tether testing and six successful free flights, including one night flight.The ALHAT sensor measurements were combined within a specialized ALHAT Navigation filter that was employed in closed-loop flight testing within the Morpheus Guidance, Navigation and Control (GN&C) subsystem. Flight testing on Morpheus utilized ALHAT for safe landing site identification and ranking, followed by precise surface-relative navigation to the selected landing site. The successful autonomous, closed-loop flight demonstrations of the prototype ALHAT system have laid the foundation for the infusion of safe, precision landing capabilities into future planetary exploration missions.

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A hybrid FPGA/Tilera compute element for autonomous hazard detection and navigation

Cited by 17 publications

References 11 publications

SA-FEMIP: A Self-Adaptive Features Extractor and Matcher IP-Core Based on Partially Reconfigurable FPGAs for Space Applications

SA-FEMIP: A Self-Adaptive Features Extractor and Matcher IP-Core Based on Partially Reconfigurable FPGAs for Space Applications

Flight testing a Real-Time Hazard Detection System for Safe Lunar Landing on the Rocket-Powered Morpheus Vehicle

Flight Testing ALHAT Precision Landing Technologies Integrated Onboard the Morpheus Rocket Vehicle

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