Unified GPU Voxel Collision Detection for Mobile Manipulation Planning

被引：0

作者：

Hermann, Andreas ^{[1
]}

Drews, Florian ^{[1
]}

Bauer, Joerg ^{[1
]}

Klemm, Sebastian ^{[1
]}

Roennau, Arne ^{[1
]}

Dillmann, Ruediger ^{[1
]}

机构：

[1] Res Ctr Informat Technol FZI, Dept Intelligent Syst & Prod Engn ISPE IDS TKS, D-76131 Karlsruhe, Germany

来源：

2014 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS 2014) | 2014年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper gives an overview on our framework for efficient collision detection in robotic applications. It unifies different data structures and algorithms that are optimized for Graphics Processing Unit (GPU) architectures. A speed-up in various planning scenarios is achieved by utilizing storage structures that meet specific demands of typical use-cases like mobile platform planning or full body planning. The system is also able to monitor the execution of motion trajectories for intruding dynamic obstacles and triggers a replanning or stops the execution. The presented collision detection is deployed in local dynamic planning with live pointcloud data as well as in global a-priori planning. Three different mobile manipulation scenarios are used to evaluate the performance of our approach.

引用

页码：4154 / 4160

页数：7

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