GPGPU computation in mobile robot applications

Bedkowski, Janusz; Masłowski, Andrzej

doi:10.15676/ijeei.2012.4.1.2

Cited by 3 publications

(3 citation statements)

References 22 publications

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“…The ICP algorithm implemented in the SLAM procedure defined for the APR mobile robots use the point to plane strategy. In general, it is well known that point to plane is a noticeably slower metric than point to point due to its complexity [ 31 ]. However, in an indoor scenario, point to plane provides better results when merging scanned point clouds that are mostly composed of straight lines (such as the large walls that conform the explored area) because it tries to align the current point cloud with the nearest planes of the 2D map rather than trying to reduce the distance between the point clouds to zero like the point to point.…”

Section: Methodsmentioning

confidence: 99%

Mobile Robot Self-Localization with 2D Push-Broom LIDAR in a 2D Map

Palacín

Martínez

Rubies

et al. 2020

Sensors

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This paper proposes mobile robot self-localization based on an onboard 2D push-broom (or tilted-down) LIDAR using a reference 2D map previously obtained with a 2D horizontal LIDAR. The hypothesis of this paper is that a 2D reference map created with a 2D horizontal LIDAR mounted on a mobile robot or in another mobile device can be used by another mobile robot to locate its location using the same 2D LIDAR tilted-down. The motivation to tilt-down a 2D LIDAR is the direct detection of holes or small objects placed on the ground that remain undetected for a fixed horizontal 2D LIDAR. The experimental evaluation of this hypothesis has demonstrated that self-localization with a 2D push-broom LIDAR is possible by detecting and deleting the ground and ceiling points from the scan data, and projecting the remaining scan points in the horizontal plane of the 2D reference map before applying a 2D self-location algorithm. Therefore, an onboard 2D push-broom LIDAR offers self-location and accurate ground supervision without requiring an additional motorized device to change the tilt of the LIDAR in order to get these two combined characteristics in a mobile robot.

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Section: Methodsmentioning

confidence: 99%

Mobile Robot Self-Localization with 2D Push-Broom LIDAR in a 2D Map

Palacín

Martínez

Rubies

et al. 2020

Sensors

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“…However, most existing parallel implementations of SVD are specialized for large matrices [29]. For SVD of a large number of small matrices, Bedkowski et al introduced an algorithm for three-dimensional reconstruction using mobile robots [30]. In the present work, the algorithm introduced by Bedkowski et al is modified.…”

Section: Additional Filementioning

confidence: 99%

GPU-accelerated surgery simulation for opening a brain fissure

et al. 2015

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In neurosurgery, dissection and retraction are basic techniques for approaching the site of pathology. These techniques are carefully performed in order to avoid damage to nerve tissues or blood vessels. However, novice surgeons cannot train in such techniques using the haptic cues of existing training systems. This paper proposes a real-time simulation scheme for training in dissection and retraction when opening a brain fissure, which is a procedure for creating a working space before treating an affected area. In this procedure, spatulas are commonly used to perform blunt dissection and brain tissue retraction. In this study, the interaction between spatulas and soft tissues is modeled on the basis of a finite element method (FEM). The deformation of soft tissue is calculated according to a corotational FEM by considering geometrical nonlinearity and element inversion. A fracture is represented by removing tetrahedrons using a novel mesh modification algorithm in order to retain the manifold property of a tetrahedral mesh. Moreover, most parts of the FEM are implemented on a graphics processing unit (GPU). This paper focuses on parallel algorithms for matrix assembly and matrix rearrangement related to FEM procedures by considering a sparse-matrix storage format. Finally, two simulations are conducted. A blunt dissection simulation is conducted in real time (less than 20 ms for a time step) using a soft-tissue model having 4807 nodes and 19,600 elements. A brain retraction simulation is conducted using a brain hemisphere model having 8647 nodes and 32,639 elements with force feedback (less than 80 ms for a time step). These results show that the proposed method is effective in simulating dissection and retraction for opening a brain fissure.

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“…e) f) g) h) Fig. 3: Operational field trials for requirements validation: a, e): Ground robots navigating indoor and outdoor on rough terrain [16]; b, f): Aerial platforms searching for human victims and doing site surveys; c, g): Maritime platforms testing deployment of rescue capsules for rescuing victims in water [13]; d): Communication tools trials [17] and h) 3D reconstruction of the environment [18]…”

Section: Operational Validation Of the User Requirements And Conclusionmentioning

confidence: 99%

Designing Search and Rescue Robots towards Realistic User Requirements

Doroftei¹,

Matos

Cubber³

2014

AMM

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Abstract. In the event of a large crisis (think about typhoon Haiyan or the Tohoku earthquake and tsunami in Japan), a primordial task of the rescue services is the search for human survivors on the incident site. This is a complex and dangerous task, which often leads to loss of lives among the human crisis managers themselves. The introduction of unmanned search and rescue devices can offer a valuable tool to save human lives and to speed up the search and rescue process. In this context, the EU-FP7-ICARUS project [1] concentrates on the development of unmanned search and rescue technologies for detecting, locating and rescuing humans. The complex nature and difficult operating conditions of search and rescue operations pose heavy constraints on the mechanical design of the unmanned platforms. In this paper, we discuss the different user requirements which have an impact of the design of the mechanical systems (air, ground and marine robots). We show how these user requirements are obtained, how they are validated, how they lead to design specifications for operational prototypes which are tested in realistic operational conditions and we show how the final mechanical design specifications are derived from these different steps. An important aspect of all these design steps which is emphasized in this paper is to always keep the end-users in the loop in order to come to realistic requirements and specifications, ensuring the practical deployability [2] of the developed platforms.

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GPGPU computation in mobile robot applications

Cited by 3 publications

References 22 publications

Mobile Robot Self-Localization with 2D Push-Broom LIDAR in a 2D Map

Mobile Robot Self-Localization with 2D Push-Broom LIDAR in a 2D Map

GPU-accelerated surgery simulation for opening a brain fissure

Designing Search and Rescue Robots towards Realistic User Requirements

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