Lidar simulation using graphics hardware acceleration

Peinecke, Niklas; Lueken, Thomas; Korn, Bernd

doi:10.1109/dasc.2008.4702838

Cited by 28 publications

(11 citation statements)

References 8 publications

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“…Since the imaging geometry of a Ladar system is more similar to an optical camera the implementation was rather straight forward. 25 The output of different sensors can be seen in figure 3. The structure of the F3S was chosen to be rather generic and modular 26 so that further simulators could be integrated like, for example, recently a 2.5D radar system and an IR imaging sensor.…”

Section: Simulation At Dlrmentioning

confidence: 99%

An evaluation test bed for enhanced vision

Doehler

Peinecke

2010

SPIE Proceedings

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DLR's Institute of Flight Guidance is involved in many projects dealing with the development of new concepts for flight procedures and pilot assistance functions. This includes especially the topic of enhanced vision (EVS), where processed data from radar and infrared sensors is utilized to augment the pilot's vision. For evaluating these concepts extensive flight testing has been conducted and results have been published during the last years. Now, DLR has combined its expertise in the field of high performance sensor simulation on the one hand side, together with the visual simulation for its generic cockpit simulator, on the other hand. Sensor simulation of imaging radar, lidar, infrared, etc., is based mainly on the application of high performance functions of modern computer graphics hardware (vertex and fragment shaders). The direct combination of these functions with the "outside-vision" software, which is now based on exactly the same terrain and object geometry, delivers sensor data that perfectly correlate to the visual channel. This combined simulation environment will be the basis for various evaluation trials within the near future, including simulation trails for fixed-wing and rotary-wing applications.The paper presents the implemented software and hardware architecture of the cockpit's visual simulator and its coupling to the sensor simulation test-suite. First results of recently conducted simulation experiments including the evaluation of new proposed flight procedures, which apply EVS technology, are given.

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Section: Simulation At Dlrmentioning

confidence: 99%

An evaluation test bed for enhanced vision

Doehler

Peinecke

2010

SPIE Proceedings

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“…Some existing work exploits general purpose computing on the GPU for mapping smaller volumes, [8], [9], and more recently with OpenCL [10] rather than directly using the GPU rendering functionality. [11] uses the GPU for quick ray triangle intersections to process laser range data, [12] tackles Lidar scan matching on the GPU, and [13] exploits the fragment and vertex shaders.…”

Section: Background and Related Work Simultaneous Localization Anmentioning

confidence: 99%

RenderMap: Exploiting the Link Between Perception and Rendering for Dense Mapping

Rydc

Ding²

2018

2018 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM)

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We introduce an approach for the real-time (2Hz) creation of a dense map and alignment of a moving robotic agent within that map by rendering using a Graphics Processing Unit (GPU). This is done by recasting the scan alignment part of the dense mapping process as a rendering task. Alignment errors are computed from rendering the scene, comparing with range data from the sensors, and minimized by an optimizer. The proposed approach takes advantage of the advances in rendering techniques for computer graphics and GPU hardware to accelerate the algorithm. Moreover, it allows one to exploit information not used in classic dense mapping algorithms such as Iterative Closest Point (ICP) by rendering interfaces between the free space, occupied space and the unknown. The proposed approach leverages directly the rendering capabilities of the GPU, in contrast to other GPU-based approaches that deploy the GPU as a general purpose parallel computation platform.We argue that the proposed concept is a general consequence of treating perception problems as inverse problems of rendering. Many perception problems can be recast into a form where much of the computation is replaced by render operations. This is not only efficient since rendering is fast, but also simpler to implement and will naturally benefit from future advancements in GPU speed and rendering techniques. Furthermore, this general concept can go beyond addressing perception problems and can be used for other problem domains such as path planning.

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“…In order to develop and test data fusion and display methods it is necessary to have ground based simulations for all sensors available that can be used in conjunction with a flight simulator. Over the recent years, DLR has developed a suite of computer graphics based realtime simulators for most of the sensors like millimeter wave radar [1] and lidar/ladar [2,3]. Within preceding projects and in the initial stages of ALLFlight this suite has already proven useful [4,5].…”

Section: Introductionmentioning

confidence: 99%

Integration of a 2.5D radar simulation in a sensor simulation suite

Peinecke

Groll

2010

29th Digital Avionics Systems Conference

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Recently DLR's sensor simulation toolkit F3S (flexible sensor simulation suite) has evolved from a mere proof-of-concept demonstrator to a versatile collection of sensor simulations. The main aspect of the software is to provide real-time simulation for sensors like millimeter wave radar and laser based sensors in an environment for testing enhanced vision concepts. We achieve this by making heavy use of graphics hardware acceleration as available in recent computer hardware.The latest addition to the set of sensor simulations is a 2.5D/3D scanning radar. Other than traditional 2D radars simulating such a sensor raises some special challenges when most of the calculations should be done by the graphics hardware.We present a custom solution that extends our previous approach to 2.5D and 3D sensors while maintaining real-time in the sense that the simulation runs at least as fast as real existing sensors.

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Lidar simulation using graphics hardware acceleration

Cited by 28 publications

References 8 publications

An evaluation test bed for enhanced vision

An evaluation test bed for enhanced vision

RenderMap: Exploiting the Link Between Perception and Rendering for Dense Mapping

Integration of a 2.5D radar simulation in a sensor simulation suite

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