Publications

kDet: Parallel Constant Time Collision Detection for Polygonal Objects

Rene Weller, Nicole Debowski and Gabriel Zachmann

We define a novel geometric predicate and a class of objects that enables us to prove a linear bound on the number of intersecting polygon pairs for colliding 3D objects in that class. Our predicate is relevant both in theory and in practice: it is easy to check and it needs to consider only the geometric properties of the individual objects - it does not depend on the configuration of a given pair of objects. In addition, it characterizes a practically relevant class of objects: we checked our predicate on a large database of real-world 3D objects and the results show that it holds for all but the most pathological ones. Our proof is constructive in that it is the basis for a novel collision detection algorithm that realizes this linear complexity also in practice. Additionally, we present a parallelization of this algorithm with a worst-case running time that is independent of the number of polygons. Our algorithm is very well suited not only for rigid but also for deformable and even topology-changing objects, because it does not require any complex data structures or pre-processing. We have implemented our algorithm on the GPU and the results show that it is able to find in real-time all colliding polygons for pairs of deformable objects consisting of more than 200k triangles, including self-collisions.

Published:

Eurographics 2017, Lyon, France, April 24 - 28, 2017. [BibTex]

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Optimized Positioning of Autonomous Surgical Lamps

Jörn Teuber, Rene Weller, Ron Kikinis, Karl-Jürgen Oldhafer, Michael J. Lipp, Gabriel Zachmann

We consider the problem of finding automatically optimal positions of surgical lamps throughout the whole surgical procedure, where we assume that future lamps could be robotized. We propose a two-tiered optimization technique for the real-time autonomous positioning of those robotized surgical lamps. Typically, finding optimal positions for surgical lamps is a multi-dimensional problem with several, in part conflicting, objectives, such as optimal lighting conditions at every point in time while minimizing the movement of the lamps in order to avoid distractions of the surgeon. Consequently, we use multi-objective optimization (MOO) to find optimal positions in real-time during the entire surgery.
Due to the conflicting objectives, there is usually not a single optimal solution for such kinds of problems, but a set of solutions that realizes a Pareto-front. When our algorithm selects a solution from this set it additionally has to consider the individual preferences of the surgeon. This is a highly non-trivial task because the relationship between the solution and the parameters is not obvious. We have developed a novel meta-optimization that considers exactly this challenge. It delivers an easy to understand set of presets for the parameters and allows a balance between the lamp movement and lamp obstruction. This meta-optimization can be pre-computed for different kinds of operations and it then used by our online optimization for the selection of the appropriate Pareto solution.
Both optimization approaches use data obtained by a depth camera that captures the surgical site but also the environment around the operating table. We have evaluated our algorithms with data recorded during a real open abdominal surgery. It is available for use for scientific purposes. The results show that our meta-optimization produces viable parameter sets for different parts of an intervention even when trained on a small portion of it.

Published:

SPIE Medical Imaging Orlando, FL, USA, February 11 - 16, 2017. [BibTex]

Copyright 2017 Society of Photo Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic electronic or print reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.

http://dx.doi.org/10.1117/12.2256029

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Knowledge Discovery for Pareto based Multiobjective Optimization in Simulation

Patrick Lange, Rene Weller, Gabriel Zachmann

We present a novel knowledge discovery approach for automatic feasible design space approximation and parameter optimization in arbitrary multiobjective blackbox simulations. Our approach does not need any supervision of simulation experts. Usually simulation experts conduct simulation experiments for a predetermined system specification by manually reducing the complexity and number of simulation runs by varying input parameters through educated assumptions and according to prior defined goals. This leads to a error-prone trial-and-error approach for determining suitable parameters for successful simulations. In contrast, our approach autonomously discovers unknown relationships in model behavior and approximates the feasible design space. Furthermore, we show how Pareto gradient information can be obtained from this design space approximation for state-of-the-art optimization algorithms. Our approach gains its efficiency from a novel spline-based sampling of the parameter space in combination within novel forest-based simulation dataflow analysis. We have applied our new method to several artificial and real-world scenarios and the results show that our approach is able to discover relationships between parameters and simulation goals. Additionally, the computed multiobjective solutions are close to the Pareto front.

Published:

ACM SIGSIM PADS , Banff, AB, Canada, May 15 - 18, 2016 [BibTex]

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GraphPool: A High Performance Data Management for 3D Simulations

Patrick Lange, Rene Weller, Gabriel Zachmann

We present a new graph-based approach called GraphPool for the generation, management and distribution of simulation states for 3D simulation applications. Currently, relational databases are often used for this task in simulation applications. In contrast, our approach combines novel wait-free nested hash map techniques with traditional graphs which results in a schema-less, in-memory, highly efficient data management. Our GraphPool stores static and dynamic parts of a simulation model, distributes changes caused by the simulation and logs the simulation run. Even more, the GraphPool supports sophisticated query types of traditional relational databases. As a consequence, our GraphPool overcomes the associated drawbacks of relational database technology for sophisticated 3D simulation applications. Our GraphPool has several advantages compared to other state-of-the-art decentralized methods, such as persistence for simulation state over time, object identification, standardized interfaces for software components as well as a consistent world model for the overall simulation system. We tested our approach in a synthetic benchmark scenario but also in real-world use cases. The results show that it outperforms state-of-the-art relational databases by several orders of magnitude.

Published:

ACM SIGSIM PADS , Banff, AB, Canada, May 15 - 18, 2016 [BibTex]

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Wait-Free Hash Maps in the Entity-Component-System Pattern for Realtime Interactive Systems

Patrick Lange, Rene Weller, Gabriel Zachmann

In the past, the Entity-Component-System (ECS) pattern has become a major design pattern used in modern architectures for Realtime Interactive Systems (RIS). In this paper we introduce high performance wait-free hash maps for the System access of Components within the ECS pattern. This allows non-locking read and write operations, leading to a highly responsive low-latency data access while maintaining a consistent data state. Furthermore, we present centralized as well as decentralized approaches for reducing the memory demand of these memory-intensive wait-free hash maps for diverse RIS applications. Our approaches gain their efficiency by Component-wise queues which use atomic markup operations for fast memory deletion. We have implemented our new method in a current RIS and the results show that our approach is able to efficiently reduce the memory usage of wait-free hash maps very effectively by more than a factor of ten while still maintaining their high performance. Furthermore, we derive best practices from our numerical results for different use cases of wait-free hash map memory management in diverse RIS applications.

Published:

IEEE VR: 9th Workshop on Software Engineering and Architectures for Realtime Interactive Systems SEARIS 2016 , Greenville, SC, USA, March 19 - 23, 2016 [BibTex]

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Kinaptic - Techniques and Insights for Creating Competitive Accessible 3D Games for Sighted and Visually Impaired Users

Andreas Grabski, Toni Toni, Tom Zigrand, Rene Weller, Gabriel Zachmann

We present the first accessible game that allows a fair competition between sighted and blind people in a shared virtual 3D environment.We use an asymmetric setup that allows touchless interaction via Kinect, for the sighted player, and haptic, wind, and surround audio feedback, for the blind player. We evaluated our game in an in-the-wild study. The results show that our setup is able to provide a mutually fun game experience while maintaining a fair winning chance for both players. Based on our study, we also suggest guidelines for future developments of games for visually impaired people that could help to further include blind people into society.

Published:

Haptics Symposium 2016, Philadelphia, PA, USA, April 8 - 11, 2016 [BibTex]

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Multi Agent System Optimization in Virtual Vehicle Testbeds

Patrick Lange, Rene Weller, Gabriel Zachmann

Modelling, simulation, and optimization play a crucial role in the development and testing of autonomous vehicles. The ability to compute, test, assess, and debug suitable configurations reduces the time and cost of vehicle development. Until now, engineers are forced to manually change vehicle configurations in virtual testbeds in order to react to inappropriate simulated vehicle performance. Such manual adjustments are very time consuming and are also often made ad-hoc, which decreases the overall quality of the vehicle engineering process. In order to avoid this manual adjustment as well as to improve the overall quality of these adjustments, we present a novel comprehensive approach to modelling, simulation, and optimization of such vehicles. Instead of manually adjusting vehicle configurations, engineers can specify simulation goals in a domain specific modelling language. The simulated vehicle performance is then mapped to these simulation goals and our multi-agent system computes for optimized vehicle configuration parameters in order to satisfy these goals. Consequently, our approach does not need any supervision and gives engineers visual feedback of their vehicle configuration expectations. Our evaluation shows that we are able to optimize vehicle configuration sets to meet simulation goals while maintaining real-time performance of the overall simulation.

Published:

EAI SIMUtools 2015, Athens, Greece, Portland, August 24 - 26, 2015.

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Scalable Concurrency Control for Massively Collaborative Virtual Environments

Patrick Lange, Rene Weller, Gabriel Zachmann

We present a novel concurrency control mechanism for collaborative massively parallel virtual environments that allows an arbitrary amount of components to exchange data with very little synchronisation overhead. The approach taken here is to maintain the shared world state of the complete virtual environment in a global key-value pool. Our novel method does not use any locking mechanism. Instead it allows wait-free data access for all concurrent components for both, reading and writing operations. This guarantees a highly responsive low-latency data access while keeping a consistent system state for all users and system components. Nevertheless, our approach is perfectly scalable even for massive multi-user scenarios. We provide a number of benchmarks in this paper, and the results show an almost constant run-time, independent of the number of concurrent users. Moreover, our approach outperforms previous concurrency control systems significantly by more than an order of magnitude.

Published:

ACM Multimedia Systems, Massively Multiuser Virtual Environments (MMVE) 2015 , Portland, United States, March 18 - 20, 2015. [BibTex]

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Massively-Parallel Proximity Queries for Point Clouds

Max Kaluschke, Uwe Zimmermann, Marinus Danzer, Gabriel Zachmann and Rene Weller

We present a novel massively-parallel algorithm that allows real-time distance computations between arbitrary 3D objects and unstructured point cloud data. Our main application scenario is collision avoidance for robots in highly dynamic environments that are recorded via a Kinect, but our algorithm can be easily generalized for other applications such as virtual reality. Basically, we represent the 3D object by a bounding volume hierarchy, therefore we adopted the Inner Sphere Trees data structure, and we process all points of the point cloud in parallel using GPU optimized traversal algorithms. Additionally, all parallel threads share a common upper bound in the minimum distance, this leads to a very high culling efficiency. We implemented our algorithm using CUDA and the results show a real-time performance for online captured point clouds. Our algorithm outperforms previous CPU-based approaches by more than an order of magnitude.

Published:

11th Workshop on Virtual Reality Interaction and Physical Simulation VRIPHYS (2014), Bremen, Germany, September 24 - 25, 2014. [BibTex]

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Massively Parallel Batch Neural Gas for Bounding Volume Hierarchy Construction

Rene Weller, David Mainzer, Abhishek Srinivas, Matthias Teschner and Gabriel Zachmann

Ordinary bounding volume hierarchy (BVH) construction algorithms create BVHs that approximate the boundary of the objects. In this paper, we present a BVH construction that instead approximates the volume of the objects with successively finer levels. It is based on Batch Neural Gas (BNG), a clustering algorithm that is known from machine learning. Additionally, we present a novel massively parallel version of this BNG-based hierarchy construction that runs completely on the GPU. It reduces the theoretical complexity of the sequential algorithm from O(nlogn) to O(log2 n) and also our CUDA implementation outperforms the CPU version significantly in practice.

Published:

11th Workshop on Virtual Reality Interaction and Physical Simulation VRIPHYS (2014), Bremen, Germany, September 24 - 25, 2014. [BibTex]

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A Framework for Wait-Free Data Exchange in Massively Threaded VR Systems

Patrick Lange, Rene Weller, Gabriel Zachmann

A central part of virtual reality systems and game engines is the generation, management and distribution of all relevant world states. In modern interactive graphic software systems usually many independent software components need to communicate and exchange data. Standard approaches suffer the n² problem because the number of interfaces grows quadratically with the number of component functionalities. Such many-to-many architectures quickly become unmaintainable, not to mention latencies of standard concurrency control mechanisms. We present a novel method to manage concurrent multithreaded access to shared data in virtual environments. Our highly efficient low-latency and lightweight architecture is based on a new wait-free hash map using key-value pairs. This allows us to reduce the traditional many-to-many problem to a simple many-to-one approach. Our results show that our framework outperforms by more than two orders of magnitude standard lock-based but also modern lock-free methods significantly.

Published:

International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision (WSCG)), Plzen, Czech Republic, June 2 - 5, 2014. ISBN 978-80-86943-71-8 [BibTex]

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Fast Sphere Packings with Adaptive Grids on the GPU

Jörn Teuber, Rene Weller, Gabriel Zachmann, Stefan Guthe

Polydisperse sphere packings are a new and very promising data representation for several fundamental problems in computer graphics and VR such as collision detection and deformable object simulation. In this paper we present acceleration techniques to compute such sphere packings for arbitrary 3D objects efficiently on the GPU. To do that, we apply different refinement methods for adaptive grids. Our results show a significant speed-up compared to existing approaches.

Published:

GI VR/AR 2013 (X. Workshop der GI-Fachgruppe VR/AR) Second Place for Best Paper Award [BibTex]

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New Geometric Data Structures for Collision Detection

Rene Weller

Published:

Extended Version: Springer Series on Touch and Haptic Systems [BibTex]
Original Version: Staats- und Universitätsbibliothek Bremen [BibTex]

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     Flyer
     Paper

User Performance in Complex Bi-manual Haptic Manipulation with 3 DOFs vs. 6 DOFs

Rene Weller, Gabriel Zachmann

Published:

Haptics Symposium 2012 [BibTex]

Files:

     Paper (pdf, 2.6MB)
     Poster (pdf, 1.6MB)
     Eyecatcher (pdf, 0.8MB)
     Teaser (pptx, 10.0MB) Best Teaser Award

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     Project Homepage

3-DOF vs. 6-DOF - Playful Evaluation of Complex Haptic Interactions

Rene Weller, Gabriel Zachmann

Published:

IEEE International Conference on Consumer Electronics (ICCE) 2011 [BibTex]

Files:

     Paper (pdf, 0.5MB)
     Slides (pptx, 15MB)
     Video from Talk: wmv (60MB), mov (76MB)

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     Project Homepage

Inner Sphere Trees and Their Application to Collision Detection

Rene Weller, Gabriel Zachmann

• A novel geometric data structure, the Inner Sphere Trees (IST), that provides hierarchical bounding volumes from the inside of an object.
• A method to compute a dense sphere packing inside a polygonal object.
• We propose to utilize a clustering algorithm to construct a sphere hierarchy.
• A unified algorithm that can compute for a pair of objects, based on their ISTs, both an approximate minimal distance and the approximate penetration volume; the application does not need to know in advance which situation currently exists between the pair of objects.
• A method to compute forces from the penetration volume that are continuous, both in direction and value.

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ProtoSphere: A GPU-Assisted Prototype Guided Sphere Packing Algorithm for Arbitrary Objects

Rene Weller, Gabriel Zachmann

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A Benchmarking Suite for 6-DOF Real Time Collision Response Algorithms

Rene Weller, David Mainzer, Gabriel Zachmann, Mikel Sagardia, Thomas Hulin, Carsten Preusche

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Stable 6-DOF Haptic Rendering with Inner Sphere Trees

Rene Weller, Gabriel Zachmann

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A Unified Approach for Physically-Based Simulations and Haptic Rendering

Rene Weller, Gabriel Zachmann

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Inner Sphere Trees for Proximity and Penetration Queries

Rene Weller, Gabriel Zachmann

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A Benchmarking Suite for Static Collision Detection Algorithms

Sven Trenkel, René Weller, Gabriel Zachmann

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Kinetic Separation Lists for Continuous Collision Detection of Deformable Objects

Published

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Kinetic Bounding Volume Hierarchies for Deformable Objects

Gabriel Zachmann, René Weller

Published

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A Model for the Expected Running Time of Collision Detection using AABB Trees

René Weller, Jan Klein, Gabriel Zachmann

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