Multi agent hybrid dynamical systems are a natural model for collaborative missions in which several steps and behaviors are required to achieve the goal of the mission. Missions are tasks featuring interacting subtasks, such as the decision of where to search, how to search, and when to transition from a search behavior to a rescue behavior. Control in hybrid systems is poorly understood. Theoretical results on state reachability rely on restrictive assumptions which hinder formal verification and optimization of such systems. Further difficulties arise if there are no a priori ordering or termination conditions on the intermediate steps and behaviors. We present a flexible framework to enable decentralized multi agent hybrid control and demonstrate its efficacy in a class of multi-region search and rescue scenarios. We also demonstrate the importance of dynamic target modeling at both levels of the hybrid state, i.e. estimating which region targets are in, how search behavior affects this estimate, and how the targets move between and within regions.
Modernization of line-of-sight communications, with beam-forming, mesh networking, and technologies making communications less detectable and susceptible to interference and jamming in contested environments help to secure lines of communications on and on the battlefield. We present a self-adjusting drone-hosted autonomous mesh network to deliver critical data in situations not historically supported by traditional configurations of radios. We develop autonomous collaboration behaviors to maintain a dynamic and adaptive tactical mesh network that ensures high quality communications in uncertain battlefield environments. While recent advances in tactical communications (e.g., 5G, optical, etc.) allow high bandwidth, directed line-of-sight (LOS) peer to peer information sharing between both manned and unmanned assets, current high-bandwidth communications infrastructures for ground and air lack the exibility to support highly dynamic and mobile operations, often requiring manned ground stations and established, planned-out infrastructure. By hosting a tactical mesh network on a swarm of mobile unmanned platforms, we extend the communications range of the network beyond LOS and around occlusions such as terrain and urban sprawl. We achieve this through a combination of rapidly exploring random graphs to identify candidate mesh configurations, non-convex genetic optimization to refine these configurations, and distributed multi-agent control algorithms to maintain the dynamic mesh in-situ. Our solution optimizes resiliency where feasible, often allowing the network to continue to function in the presence of a dead or otherwise compromised agent.
We take the first step to demonstrate the feasibility of using Modular, Extensible, Interoperable Autonomy (MEIA) to support the Internet of Military Things (IoMT) by implementing MEIA for an Aurelia drone. We set up a pipeline for autonomy development (PAD) which includes tools and processes that facilitate autonomy development. We implement both the middleware and internal data management to run our MEIA solution which includes the autonomy algorithms capable of executing various missions. We provide the results of our final demonstrations which mark the completion of this initial step to demonstrate MEIA as a viable cross-domain, autonomy architecture for IoMT.
As warfare looks to the future and the need for the internet of military things (IoMT) grows, we discuss how autonomy fits into this paradigm. We define common terms relating to autonomy to promote common understanding between autonomy developers, and we analyze a variety of autonomy architectures, examining what they do correctly to support IoMT and where they fall short. We discuss our general philosophy concerning autonomy – that it must be multi-layered to be effective – and provide an overview for our Modular, Extensible, Interoperable Autonomy architecture that supports IoMT and the future of warfare.
Control in multi-agent hybrid dynamical systems – systems in which the state contains both discrete and continuous elements – is poorly understood. Theoretical results on state reachability and avoidablility typically rely on restrictive assumptions which do not hold in many important cases, hampering results in both trust and optimization of such systems. We introduce a flexible framework to enable control in multi-agent hybrid dynamical systems. We present an agent-based finite horizon temporal logic (FHTL) framework that enables mission monitoring and improves agent to agent collaboration in multi-agent hybrid systems under significantly lighter assumptions than required for similar infinite horizon temporal logic (IHTL) applications. We demonstrate our framework in an example scenario and provide both quantitative and qualitative analyses of the performance gains and mission trust monitoring enabled by our tools for this example.
Game-theoretic analysis allows for systematic analysis of complex adversarial situations modelled as extensive form games. Counterfactual regret minimization, the leading game-theoretic framework used to solve extensive form games, is generally used to develop improved and unexploitable decision agents. This paper focuses on the third-party planner – an agent with a stake in the outcome of a game yet have no agency within the game. Third-party planners include game organizers trying to anticipate game situations for broadcast and planning, those providing logistical support to the players, or anyone else who might interact with the game environment. While projecting game flow might in general be quite difficult, the problem becomes tractable if the players are sufficiently sophisticated as to follow an approximate equilibrium solution. This paper demonstrates how counterfactual regret minimization can assist third party planners under these circumstances.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.