MPSoC4Drones: An Open Framework for ROS2, PX4, and FPGA Integration

Abstract

Autonomous drones are facing a tough efficiency challenge due to limitations on the utilized processing hardware units. Among these limitations is the tradeoff between fast computing and low power consumption; between functional complexity and flight time. Recent progressions point to FPGAs for accelerating heavy processing. In this work, we present the MPSoC4Drones Framework; a novel framework for organizing FPGA-design and OS build projects. The framework combines tools for creating bootable images for the Ultra96-V2 board.We show how MPSoC4Drones organizes the build, combining the latest well-known tools for research and industrial drone development, Ubuntu 20.04, PX4 autopilot, and ROS2 middleware. We validate the framework through a computationally intensive deep learning use case implemented in the MPSoC4Drones framework. We show the superior throughput and low power consumption of FPGA processing compared to classical CPU and GPU approaches. Finally, we offer the full framework as open-source.

Heterogeneous Flight Management System (FMS) Design for Unmanned Aerial Vehicles (UAVs): Current Stages, Challenges, and Opportunities

“…Furthermore, it is suitable for TinyML-based acceleration on FPGA in terms of Processing-in-Memory (PIM) architecture [67]. However, working with FPGAs requires a deep understanding of hardware logic, creating a barrier to their adoption in aerial robotic communities [10].…”

“…In contrast to the Flight Control System (FCS), the FMS provides advances to improve flight safety and economy effectively. Figure 1 illustrates an exemplary comparison between FCS and FMS [10]. Generally, the FCS is deployed as the primary component for UAV control, such as CUAV V5+ in Figure 1a and Flight Controller PX4 in Figure 1b.…”

Onboard Powerline Perception System for UAVs Using mmWave Radar and FPGA-Accelerated Vision

“…Additionally, none of the methods have been demonstrated to run onboard a UAV in real-time. Because of their power efficiency and high throughput capability, FPGAs have been used on UAVs as flight controllers [40], neural network accelerators [41], [42], and generally deployed for their reconfigurability [43], [44]. NASA's Mars UAV [45] uses FPGAs for flight control, fault tolerance, and as IO and communications hubs.…”

“…The Ultra96-V2 onboard computer [53] features a quad-core application CPU (APU) with 2GB of RAM as well as FPGA fabric and Advanced eXtensible Interface (AXI) bus intra-chip communication infrastructure. Setting up the onboard computer for autonomous drone operations is non-trivial and time consuming, and the MPSoC4Drones framework [54] exists to ease this process on the Ultra96-V2 single-board computer. The framework targets applications using an external PX4 flight controller and creates bootable images with Ubuntu 20.04, ROS2, PX4 communication, drivers, and custom programmable logic designs.…”

“…Here, it is connected to the CPU via the AXI bus and memory addresses are assigned to it, which are used to read from and write to the accelerator from software, where it appears as a device file in the Ubuntu operating system. For more information, see our previous MPSoC4Drones work [54].…”