A Contribution to Resource-Aware Architectures for Humanoid RobotsThe goal of this work is to provide building blocks for resource-aware robot architectures. The topic of these blocks are data-driven generation of context-sensitive resource models, prediction of future resource utilizations, and resource-aware computer vision and motion planning algorithms. The implementation of these algorithms is based on resource-aware concepts and methodologies originating from the Transregional Collaborative Research Center ""Invasive Computing"" (SFB/TR 89). |
Common terms and phrases
adapting Additionally application model approach ARMAR-III ArmarX basic resource models behavior calculated configuration context context-sensitive resource models control flow CPU and memory CPU CPU CPU CPU utilization Cspace Dataset described disparity map algorithm distributed environment evaluated execution future robot tasks GNU C library hardware humanoid robots implementation interfaces Invasive Computing Kröhnert Linux Linux kernel main memory Markov chain memory utilization MemoryX middleware motion planning motion planning algorithm multi-core Network on Chip nodes OctoPOS operating system parallel parameters performed Pick And Place place task planning problem prediction model processors provides real-time requested resource allocation strategies resource demands Resource Prediction resource utilization resource-aware Ressourcen robot application robot architectures robot components robot framework RRT algorithm runtime sampling search tree sensor shown in Figure software architectures specific speculative resource management started sub-state tion transition probabilities tsolve Valgrind visual servo Voronoi Diagram Voronoi region Wavg Wmax worker processes