Mosquito-inspired Swarming and Pursuit for Autonomous Rotorcraft

The long-term goal of this research is to design cooperative-control algorithms for autonomous vehicles inspired by the collective behaviors in animal groups. The specific research objectives of this dissertation are twofold: (1) to analyze and model the swarming and pursuit behaviors observed in the mating swarms of mosquitoes, and (2) to design mosquito-inspired control algorithms to perform swarming and pursuit with autonomous rotorcraft. The first part of this dissertation analyzes the reconstructed flight data of the malarial mosquito Anopheles gambiae to characterize the velocity-alignment interaction between male mosquitoes, who aggregate to form mating swarms and subsequently pursue a female mosquito. Both swarming and pursuit behaviors are represented using self-propelled particle models. The model is used together with tools from control theory to investigate the connection between velocity-alignment behavior and success in pursuit. The results of this research have a potential impact on vector-control methods for malaria, and are also utilized in the second part of this dissertation. The second part of this dissertation studies two types of pursuit problems inspired by the collective behavior in mosquito swarms. The first problem considers the strategy for a single pursuer chasing a single target. This problem has been studied extensively for the application to missile guidance and navigation. Here, we tailor the assumptions on the dynamics of the agents as well as the design criteria for the application to small and agile rotorcraft. The second pursuit problem incorporates the swarming behavior by considering a scenario in which multiple guardian vehicles are deployed to protect an area against fast intruders. We derive necessary and sufficient conditions for capturing the intruder. We also present swarming strategies to maximize the performance of the guardians, inspired by the random-oscillatory motion and the velocity-alignment behavior of male mosquitoes

Decentralization of Multiagent Policies by Learning What to Communicate

Effective communication is required for teams of robots to solve sophisticated collaborative tasks. In practice it is typical for both the encoding and semantics of communication to be manually defined by an expert; this is true regardless of whether the behaviors themselves are bespoke, optimization based, or learned. We present an agent architecture and training methodology using neural networks to learn task-oriented communication semantics based on the example of a communication-unaware expert policy. A perimeter defense game illustrates the system's ability to handle dynamically changing numbers of agents and its graceful degradation in performance as communication constraints are tightened or the expert's observability assumptions are broken.Comment: 7 page

Asymptotic Stability of Active Disturbance Rejection Control for Linear SISO Plants with Low Observer Gains

This paper theoretically investigates the closed-loop performance of active disturbance rejection control (ADRC) on a third-order linear plant with relative degree 3, subject to a class of exogenous disturbances. While PID control cannot be guaranteed to be capable of stabilizing such plants, ADRC offers a model-free alternative. However, many existing works on ADRC consider the observer gains to be taken arbitrarily large, in order to guarantee desired performance, such as works which consider parameterizing ADRC by bandwidth. This work finds that, for constant exogenous disturbances, arbitrary eigenvalue assignment is possible for the closed-loop system under linear ADRC, thus guaranteeing the existence of an ADRC controller for desired performance without taking any gains arbitrarily large. We also find that stabilization is possible when the exogenous disturbance is stable, and show how ADRC can recover the performance of model-based observers. We demonstrate aspects of the resulting closed-loop systems under ADRC in simulations

Guarding a Non-Maneuverable Translating Line with an Attached Defender

In this paper we consider a target-guarding differential game where the defender must protect a linearly translating line-segment by intercepting an attacker who tries to reach it. In contrast to common target-guarding problems, we assume that the defender is attached to the target and moves along with it. This assumption affects the defenders' maximum speed in inertial frame, which depends on the target's direction of motion. Zero-sum differential game of degree for both the attacker-win and defender-win scenarios are studied, where the payoff is defined to be the distance between the two agents at the time of game termination. We derive the equilibrium strategies and the Value function by leveraging the solution for the infinite-length target scenario. The zero-level set of this Value function provides the barrier surface that divides the state space into defender-win and attacker-win regions. We present simulation results to demonstrate the theoretical results.Comment: 8 pages, 8 figures. arXiv admin note: text overlap with arXiv:2207.0409

The Eater and the Mover Game

This paper studies the idea of ``deception by motion'' through a two-player dynamic game played between a Mover who must retrieve resources at a goal location, and an Eater who can consume resources at two candidate goals. The Mover seeks to minimize the resource consumption at the true goal, and the Eater tries to maximize it. While the Mover has the knowledge about the true goal, the Eater cannot differentiate between the two candidates. Unlike existing works on deceptive motion control that measures the deceptiveness through the quality of inference made by a distant observer (an estimator), we incorporate their actions to directly measure the efficacy of deception through the outcome of the game. An equilibrium concept is then proposed without the notion of an estimator. We further identify a pair of equilibrium strategies and demonstrate that if the Eater optimizes for the worst-case scenario, hiding the intention (deception by ambiguity) is still effective, whereas trying to fake the true goal (deception by exaggeration) is not.Comment: Submitted to the IEEE Control Systems Letters (L-CSS), 202

Dynamic Adversarial Resource Allocation: the dDAB Game

This work proposes a dynamic and adversarial resource allocation problem in a graph environment, which is referred to as the dynamic Defender-Attacker Blotto (dDAB) game. A team of defender robots is tasked to ensure numerical advantage at every node in the graph against a team of attacker robots. The engagement is formulated as a discrete-time dynamic game, where the two teams reallocate their robots in sequence and each robot can move at most one hop at each time step. The game terminates with the attacker's victory if any node has more attacker robots than defender robots. Our goal is to identify the necessary and sufficient number of defender robots to guarantee defense. Through a reachability analysis, we first solve the problem for the case where the attacker team stays as a single group. The results are then generalized to the case where the attacker team can freely split and merge into subteams. Crucially, our analysis indicates that there is no incentive for the attacker team to split, which significantly reduces the search space for the attacker's winning strategies and also enables us to design defender counter-strategies using superposition. We also present an efficient numerical algorithm to identify the necessary and sufficient number of defender robots to defend a given graph. Finally, we present illustrative examples to verify the efficacy of the proposed framework

Path Defense in Dynamic Defender-Attacker Blotto Games (dDAB) with Limited Information

We consider a path guarding problem in dynamic Defender-Attacker Blotto games (dDAB), where a team of robots must defend a path in a graph against adversarial agents. Multi-robot systems are particularly well suited to this application, as recent work has shown the effectiveness of these systems in related areas such as perimeter defense and surveillance. When designing a defender policy that guarantees the defense of a path, information about the adversary and the environment can be helpful and may reduce the number of resources required by the defender to achieve a sufficient level of security. In this work, we characterize the necessary and sufficient number of assets needed to guarantee the defense of a shortest path between two nodes in dDAB games when the defender can only detect assets within $k$-hops of a shortest path. By characterizing the relationship between sensing horizon and required resources, we show that increasing the sensing capability of the defender greatly reduces the number of defender assets needed to defend the path