Unmanned Systems Technology 027 l Hummingbird XRP l Gimbals l UAVs insight l AUVSI report part 2 l O’Neill Power Systems NorEaster l Kratos Defense ATMA l Performance Monitoring l Kongsberg Maritime Sounder

Dr Donough Wilson Dr Wilson is innovation lead at aviation, defence, and homeland security innovation consultants, VIVID/futureVision. His defence innovations include the cockpit vision system that protects military aircrew from asymmetric high-energy laser attack. He was first to propose the automatic tracking and satellite download of airliner black box and cockpit voice recorder data in the event of an airliner’s unplanned excursion from its assigned flight level or track. For his ‘outstanding and practical contribution to the safer operation of aircraft’ he was awarded The Sir James Martin Award 2018/19, by the Honourable Company of Air Pilots. Paul Weighell Paul has been involved with electronics, computer design and programming since 1966. He has worked in the real-time and failsafe data acquisition and automation industry using mainframes, minis, micros and cloud-based hardware on applications as diverse as defence, Siberian gas pipeline control, UK nuclear power, robotics, the Thames Barrier, Formula One and automated financial trading systems. Ian Williams-Wynn Ian has been involved with unmanned and autonomous systems for more than 20 years. He started his career in the military, working with early prototype unmanned systems and exploiting imagery from a range of unmanned systems from global suppliers. He has also been involved in ground-breaking research including novel power and propulsion systems, sensor technologies, communications, avionics and physical platforms. His experience covers a broad spectrum of domains from space, air, maritime and ground, and in both defence and civil applications including, more recently, connected autonomous cars. Unmanned Systems Technology’s consultants Sensor maker Acienna has developed an IMU with an interface to the CAN system commonly used in autonomous systems (writes Nick Flaherty). The OpenIMU300RI is a nine-axis MEMS-based IMU that includes a CAN interface, an RS-232 interface, and an ARM Coretex M4 CPU. The OpenIMU’s CPU can run both standard and custom algorithms created using an open source set of development tool. In an autonomous vehicle, CAN is used to pass IMU data to other sensors as well as the main vehicle control, and some designs are using CAN bus to share IMU data with up to 20 other vehicle subsystems in parallel, such as Lidar, image cameras and radar. The CAN specification has two standards for messages: CAN 2.0A with an 11-bit message identifier, and an alternative standard, CAN 2.0B, with a 29-bit message identifier. Both message types have a maximum data payload of only 8 bytes. Standard CAN data rates are 250 kbit/s, 500 kbit/s and 1 Mbit/s. Driverless cars tend to use custom- defined messages with 11-bit identifiers, whereas heavy equipment vehicles more commonly use the 29-bit identifiers and define messages according to the J1939 standard. Recently some applications have started to use a newer CAN FD (Flexible Data-rate) protocol that supports data payloads up to 64 bytes. That makes a CAN interface an increasingly convenient and reliable way to pass IMU data to one or more subsystems on the vehicle. The open source approach allows engineers to write an application that can ‘listen’ to other messages on the bus. For example, Acienna’s Dynamic Tilt algorithm could be enhanced by listening to messages such as odometer or vehicle speed to better compensate for the influence of linear acceleration on dynamic roll and pitch. The application could also take data from the RS-232 port on the IMU from a GNSS satellite positioning sensor. This data can then be fused with the OpenIMU300RI’s internal IMU data for full GNSS/INS sensor fusion. IMU with CAN-do Sensors The OpenIMU300RI CAN bus IMU has an open source comms and navigation stack August/September 2019 | Unmanned Systems Technology 16 Platform one