Investigation of the Tilera processor for real time hazard detection and avoidance on the Altair Lunar Lander

Villalpando, Carlos Y.; Johnson, Andrew; Some, Raphael; Oberlin, Jacob; Goldberg, Steven B.

doi:10.1109/aero.2010.5447023

Cited by 19 publications

(11 citation statements)

References 2 publications

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“…The Tilera Tile64 has been investigated as a suitable target architecture for real time hazard detection on the Altair lunar lander. 8 Here the Tile64 was used to process images from LIDAR laser 3D range measurements in order to detect hazards on a landing surface. The hazard detection processing was distributed across many cores and the Tile64's performance was analyzed.…”

Section: Related Workmentioning

confidence: 99%

Performance evaluation of canny edge detection on a tiled multicore architecture

et al. 2011

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In the last few years, a variety of multicore architectures have been used to parallelize image processing applications. In this paper, we focus on assessing the parallel speed-ups of different Canny edge detection parallelization strategies on the Tile64, a tiled multicore architecture developed by the Tilera Corporation. Included in these strategies are different ways Canny edge detection can be parallelized, as well as differences in data management. The two parallelization strategies examined were loop-level parallelism and domain decomposition. Loop-level parallelism is achieved through the use of OpenMP, 1 and it is capable of parallelization across the range of values over which a loop iterates. Domain decomposition is the process of breaking down an image into subimages, where each subimage is processed independently, in parallel. The results of the two strategies show that for the same number of threads, programmer implemented, domain decomposition exhibits higher speed-ups than the compiler managed, loop-level parallelism implemented with OpenMP.

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Section: Related Workmentioning

confidence: 99%

Performance evaluation of canny edge detection on a tiled multicore architecture

et al. 2011

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“…Algorithmic optimizations made for real-time operations include discretizing the roughness to centimeter levels and then using pre-computed table of corresponding probability values, conservatively grouping neighboring roughness values in 5x5 or 10x10 pixel windows, excluding some infeasible orientations, sparsely computing candidate landing sites at 1m intervals, and using separable Gaussian kernels in convolution with the navigation uncertainty. Furthermore, a real-time parallelized version of the HDA algorithm was implemented in C to run on the Tilera Tile64 multi-core processor [38,39].…”

Section: Optimizationsmentioning

confidence: 99%

Probabilistic Hazard Detection for Autonomous Safe Landing

Ivanov

Huertas

Carson

2013

AIAA Guidance, Navigation, and Control (GNC) Conference

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Future generation of landing craft will autonomously look at the surface during the terminal phase of powered descent and then, in real-time, choose and divert to a safe landing site in order to avoid hazards. Enabling technologies for such capability have been under development in recent years in the Autonomous Landing Hazard Avoidance Technology (ALHAT) project funded by NASA's Exploration Technology Development Program.ALHAT is a comprehensive system that spans the approach and landing events -from de-orbit coasting to touchdown. In this paper, we focus on ALHAT's perception task of detecting hazards in the sensed terrain and of selecting candidate safe sites for landing. This task, named Hazard Detection and Avoidance (HDA), occurs in the middle of the landing sequence. Our approach to HDA employs a probabilistic model in order to better manage the ubiquitous uncertainties associated with noisy sensor measurements and navigation. Also, we explicitly take into account the geometry of the lander and its interaction with the surface when assessing hazards. Experimental results on synthetic Lunar-like terrain show that our HDA algorithm can designate safe landing locations for a variety of terrain types and density and abundance of hazards. The complete ALHAT system is undergoing ground field-testing, and is scheduled for additional field tests on a one-hectare, lunar-like, hazard field recently constructed at NASA's Kennedy Space Center (KSC). Although the focus of ALHAT is on autonomous planetary landings, a number of terrestrial applications can also benefit from out HDA system.

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“…To this end, the ALHA T program conducted several studies with numerous field campaigns to determine what the ideal sensors, algorithms, and processing capabilities should be for a terrain sensing/hazard detection system (HDS) [2][3][4][5][6][7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

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

Villalpando

Werner

Carson

et al. 2013

2013 IEEE Aerospace Conference

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To increase safety for future missions landing on other planetary or lunar bodies, the Autonomous Landing and Hazard Avoidance Technology (ALHA T) program is developing an integrated sensor for autonomous surface analysis and hazard determination. The ALHAT Hazard Detection System (HDS) consists of a Flash LIDAR for measuring the topography of the landing site, a gimbal to scan across the terrain, and an Inertial Measurement Unit (IMU), along with terrain analysis algorithms to identify the landing site and the local hazards. An FPGA and Manycore processor system was developed to interface all the devices in the HDS, to provide high-resolution timing to accurately measure system state, and to run the surface analysis algorithms quickly and efficiently. In this paper, we will describe how we integrated COTS components such as an FPGA evaluation board, a TILExpress64, and multi-threaded/multi-core aware software to build the HDS Compute Element (HDSCE). The ALHAT program is also working with the NASA Morpheus Project and has integrated the HDS as a sensor on the Morpheus Lander.This paper will also describe how the HDS is integrated with the Morpheus lander and the results of the initial test flights with the HDS installed. We will also describe future improvements to the HDSCE.

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Investigation of the Tilera processor for real time hazard detection and avoidance on the Altair Lunar Lander

Cited by 19 publications

References 2 publications

Performance evaluation of canny edge detection on a tiled multicore architecture

Performance evaluation of canny edge detection on a tiled multicore architecture

Probabilistic Hazard Detection for Autonomous Safe Landing

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

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