Efficient Large-Scale Sweep and Prune Methods with AABB Insertion and Removal

Tracy, Daniel J.; Buss, Samuel R.; Woods, Bryan M.

doi:10.1109/vr.2009.4811022

Cited by 33 publications

(49 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Works of Moore et al [17], Kasper Fauerby [6], Lin et al [13], and Tracy et al [31] present the basics for object collision detection system with short references to theoretical foundations and principles of Sweep and Prune algorithm. Methods and theoretical guidelines found in those studies are used for implementation of a system that simulates the human horizontal visual field.…”

Section: Collision Detection In Two-dimensional Spaces and Visual Fiementioning

confidence: 99%

A system for deductive prediction and analysis of movement of basketball referees

Pecev

Racković

Ivković

2015

Multimed Tools Appl

View full text Add to dashboard Cite

This paper presents us with an automatic prediction and analysis of basketball referees movement which is useful for educational software. Such software would be very beneficial in training the young basketball referees. The paper proposes that the movement prediction of basketball referees can be achieved with a multilayered perceptron neural network. Network will reason on the basis of a ball movement during a play action. Proposed neural network will be trained with a modified Back Propagation algorithm which essentially presents a special algorithm for a multiple dependent Time Series prediction. In this paper, we will also describe initial designs of a neural network structure that, we believe, would better suit the nature of a multiple dependent Time Series prediction problems. The aforementioned educational software is capable of determining whether a referee was moving properly in a certain situation or not. Determination is possible on the basis of numerical values that are calculated by simulating the human visual field. The referee's horizontal field of view simulation is based on the standard set by the American Optometric Association. It is implemented through a modified Sweep and Prune algorithm which is also discussed in this paper.Keywords Multiple dependent time series · MLP neural networks · LTR -MDTS model · Field of vision simulation · Basketball referee movement Predrag Pecev

show abstract

Section: Collision Detection In Two-dimensional Spaces and Visual Fiementioning

confidence: 99%

A system for deductive prediction and analysis of movement of basketball referees

Pecev

Racković

Ivković

2015

Multimed Tools Appl

View full text Add to dashboard Cite

show abstract

“…Scenarios with many moving objects result in significant increases in s that lead to decreases in throughput. Tracy, Buss and Woods [40] demonstrate that scenarios with few moving objects can also perform poorly if the total number of objects is very high. Only all-pairs facilitates the accurate deduction of the most complex scenario that can be executed within a given timeframe, without concern that the frame rate will decrease in certain scenarios.…”

Section: Cell-based Broad Phasementioning

confidence: 99%

A hybrid fixed-function and microprocessor solution for high-throughput broad-phase collision detection

Woulfe

Manzke

2016

J Embedded Systems

View full text Add to dashboard Cite

We present a hybrid system spanning a fixed-function microarchitecture and a general-purpose microprocessor, designed to amplify the throughput and decrease the power dissipation of collision detection relative to what can be achieved using CPUs or GPUs alone. The primary component is one of the two novel microarchitectures designed to perform the principal elements of broad-phase collision detection. Both microarchitectures consist of pipelines comprising a plurality of memories, which rearrange the input into a format that maximises parallelism and bandwidth. The two microarchitectures are combined with the remainder of the system through an original method for sharing data between a ray tracer and the collision-detection microarchitectures to minimise data structure construction costs. We effectively demonstrate our system using several benchmarks of varying object counts. These benchmarks reveal that, for over one million objects, our design achieves an acceleration of 812× relative to a CPU and an acceleration of 161× relative to a GPU. We also achieve energy efficiencies that enable the mitigation of silicon power-density challenges, while making the design amenable to both mobile and wearable computing devices.

show abstract

“…For example, interval trees [11] are used in sweep-and-prune (SaP) based broadphase algorithms; spatial partitioning trees such as octrees and k-d trees can also be used [12]; hash tables are used in spatial-hashing based approaches [10]. These broad-phase data structures are designed so they can be updated efficiently when the underlying objects change their positions or when objects are added into or removed from the environment.…”

Section: Problem Definition and Related Workmentioning

confidence: 99%

Real-time collision detection and distance computation on point cloud sensor data

Pan

Sucan

Chitta

et al. 2013

2013 IEEE International Conference on Robotics and Automation

View full text Add to dashboard Cite

Most prior techniques for proximity computations are designed for synthetic models and assume exact geometric representations. However, real robots construct representations of the environment using their sensors, and the generated representations are more cluttered and less precise than synthetic models. Furthermore, this sensor data is updated at high frequency. In this paper, we present new collision-and distancequery algorithms, which can efficiently handle large amounts of point cloud sensor data received at real-time rates. We present two novel techniques to accelerate the computation of broadphase data structures: 1) we present a progressive technique that incrementally computes a high-quality dynamic AABB tree for fast culling, and 2) we directly use an octree representation of the point cloud data as a proximity data structure. We assign a probability value to each leaf node of the tree, and the algorithm computes the nodes corresponding to high collision probability. In practice, our new approaches can be an order of magnitude faster than previous methods. We demonstrate the performance of the new methods on both synthetic data and on sensor data collected using a Kinect TM for motion planning for a mobile manipulator robot.

show abstract

Efficient Large-Scale Sweep and Prune Methods with AABB Insertion and Removal

Cited by 33 publications

References 20 publications

A system for deductive prediction and analysis of movement of basketball referees

A system for deductive prediction and analysis of movement of basketball referees

A hybrid fixed-function and microprocessor solution for high-throughput broad-phase collision detection

Real-time collision detection and distance computation on point cloud sensor data

Contact Info

Product

Resources

About