However, LiDAR is imperative for waypoint navigation every time unmanned vehicles have to enter complex and unpredictable environments. The problem is that LiDAR has its limits too, i.e. that its reliability can only be guaranteed for unmanned vehicles operating in semi-complex terrain.
Hence the need for further research and development in this domain. To that end, several technology demonstrators have been developed – for example ADM-H or EuroSWARM – with a view to exploring, testing and demonstrating more advanced functions, including autonomous navigation or cooperation of unmanned systems. These demonstrators, however, are still at an early research phase.
Many challenges ahead
Limited LiDAR is not the only challenge that unmanned ground vehicles are facing. According to the Unmanned Ground Systems Landscaping and Integration Study (UGS LIS), funded by the European Defence Agency (EDA), as well as another EDA-financed study on the ‘Identification of all major technical and safet y requirements for militar y unmanned vehicle to operate in combined manned-unmanned mission’ (SafeMUVe), the challenges and opportunities can be divided into five different categories:
1. Operational: There are plenty of potential missions that can be envisaged for unmanne d ground vehicles wi t h autonomous functions (communication node, area surveillance, zone and route reconnaissance, casualty extraction, CBRN reconnaissance, follower mule, convoying for the distribution of supplies, route clearance, etc.), but operational concepts to back and underpin these are still lacking. It is therefore difficult for developers of unmanned ground vehicles with autonomous functions to develop systems which for sure will meet military requirements. Creating a forum or working group of defence users of unmanned ground systems with autonomous functions could solve this problem.
2. Technical: The potential benefits of unmanned ground vehicles with autonomous functions are considerable, but so are the technical hurdles still to overcome. Depending on the envisaged mission, unmanned ground vehicles can be equipped with different payload suites (sensors for ISR or CBRN monitoring and detection, manipulators for explosives handing or weapon systems, navigation and guidance systems...), intelligence kits, operator control suites and control hardware. This means that several enabling technologies, such as decision making/ cognitive computing, human machine interaction, computer vision, state of battery technologies or collaborative intelligence, are absolutely critical. In par ticular, unstructured and contested environments pose huge challenges to both navigation and guidance sensors. Here, the way forward has to include the development of new sensors (quantum positioning, ultra-cold atom interferometers, smart G&C actuators…) and techniques such as decentralised and cooperative SLAM (Simultaneous Localization and Mapping) and 3D mapping, relative navigation, advanced hybridisation and data-fusion of available sensors as well as vision/IR aided mobility. The problem is not so much of a technological nature – because most of these technologies are already used in civilian applications – but rather of a regulatory order. Indeed, such technologies cannot immediately be used for military purposes as they need to be adapted to specific military requirements. Against this backdrop, the EDA’s Overarching Strategic Research Agenda (OSRA) is a tool that can deliver this missing piece. Under OSRA, several so-called Technology Building Blocks (TBBs) are being developed, addressing technology gaps related to unmanned ground vehicles, for instance: – Manned/unmanned teaming, adaptive cooperation between man and unmanned system with different levels of autonomy; Health and usage monitoring; Novel User Interfaces for Soldier (assets integration/ control); Nav igation in GNS S denied environment; Autonomous and automated GNC and Decision Making techniques for manned and unmanned systems; Multirobot Control and Cooperation; Precision guidance and control of weapons; Active imaging systems; Artificial Intelligence and Big Data for Decision Making Support. Each TBB is owned by a dedicated panel (called CapTech) composed of governmental, research and industrial experts. Each CapTech will develop a roadmap for each TBB.
3. Normative/Legal: An important obstacle for the introduction of autonomous systems in defence is the lack of suitable verification and evaluation procedures or certification processes which can be used to prove that even the most basic unmanned ground vehicle with autonomous functions is able to operate correctly and safely, even in hostile and complex environments. In the civil domain, self-driving cars are facing the same problems. According to EDA’s SafeMUVe study, the main gaps identified with respect to specific standards/best practices are concentrated in the modules related to the higher layer of autonomy, namely ‘Automation’ and ‘Data fusion’ aspects. Modules such as ‘Environment perception’, ‘Localization & mapping’, ‘Supervision’ (Decision-making), ‘Motion planning’, etc. are still in mid technology readiness levels (TRLs), and although several solutions and algorithms exist to perform the different tasks, no standards are yet available. In this sense, there is also a gap in terms of verification and certification of these modules, partly addressed by the EU funded European Initiative to Enable Validation for Highly Automated Safe and Secure Systems (ENABLE-S3) project. The recent establishment, by the EDA Steering Board, of a Land Test Centres Network of Excellence (LTE) is a first step in the right direction. The LTE allows national test centres to undertake joint initiatives in view of preparing the testing of future technologies, such as automotive systems and robotics.