Task Mapping for Hardware-Accelerated Robotics Applications using ReconROS

Abstract

Modern software architectures for robotics map tasks to heterogeneous computing platforms comprising multi-core CPUs, GPUs, and FPGAs. FPGAs promise huge potential for energy efficient and fast computation, but their use in robotics requires profound knowledge of hardware design and is thus challenging. ReconROS, a combination of the reconfigurable operating system ReconOS and the robot operating system (ROS) aims to overcome this challenge with a consistent programming model across the hardware/software boundary and support of event-driven programming. In this paper, we summarize different approaches for mapping tasks to computational resources in ReconROS. These approaches include static and dynamic mappings, and the exploitation of data parallelism for single ROS nodes. Further, for dynamic mapping we propose and analyse different replacement strategies for hardware nodes to minimize reconfiguration overhead. We evaluate the presented techniques and illustrate ReconROS’ capabilites through an autonomous vehicle example in a hardware-in-the-loop simulation.