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This paper presents ModelMap, a model-based multi-domain application development framework for DriveOS, our in-house centralized vehicle management software system. DriveOS runs on multicore x86 machines and uses hardware virtualization to host isolated RTOS and Linux guest OS sandboxes. In this work, we design Simulink interfaces for model-based vehicle control function development across multiple sandboxed domains in DriveOS. ModelMap provides abstractions to: (1) automatically generate periodic tasks bound to threads in different OS domains, (2) establish cross-domain synchronous and asynchronous communication interfaces, and (3) handle USB-based CAN I/O in Simulink. We introduce the concept of a nested binary, for the deployment of ELF binary executable code in different sandboxed domains. We demonstrate ModelMap using a combination of synthetic benchmarks, and experiments with Simulink models of a CAN Gateway and HVAC service running on an electric car. ModelMap eases the development of applications, which are shown to achieve industry-target performance using a multicore hardware platform in DriveOS.

Autonomous multicopters often feature federated architectures, which incur relatively high communication costs between separate hardware components. These costs limit the ability to react quickly to new mission objectives. Additionally, federated architectures are not easily upgraded without introducing new hardware that impacts size, weight, power and cost (SWaP-C) constraints. In turn, such constraints restrict the use of redundant hardware to handle faults. In response to these challenges, we propose FlyOS, an Integrated Modular Avionics (IMA) approach to consolidate mixed-criticality flight functions in software on heterogeneous multicore aerial platforms. FlyOS is based on a separation kernel that statically partitions resources among virtualized sandboxed OSes. We present a dual-sandbox prototype configuration, where timing-and safety-critical flight control tasks execute in a real-time OS alongside mission-critical vision-based navigation tasks in a Linux sandbox. Low latency shared memory communication allows flight commands and data to be relayed in real-time between sandboxes. A hypervisor-based fault-tolerance mechanism is also deployed to ensure failover flight control in case of critical function or timing failures. We validate FlyOS’s performance and showcase its benefits when compared against traditional architectures in terms of predictable, extensible and efficient flight control.

Multi-rotor drones require real-time sensor data processing and control to maintain flight stability, which is made more challenging by external disturbances such as wind. In this paper we introduce smARTflight: an environmentally-aware adaptive real-time flight management system. smARTflight adapts the execution frequencies of flight control tasks according to timing and safety-critical constraints, in response to transient fluctuations of a drone’s attitude. In contrast to current state-of-the-art methods, smARTflight’s criticality-aware scheduler reduces the latency to return to a steady-state target attitude. The system also improves the overall control accuracy and lowers the frequency of adjustments to motor speeds to conserve power. A comparative case-study with a well-known autopilot shows that smARTflight reduces unnecessary control loop executions under stable conditions, while reducing response time latency by as much as 60% in a given axis of rotation when subjected to a 15° step attitude disturbance.