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Alexander Von Moll

Publications and source records attributed to Alexander Von Moll.

At least 19 recordsLinked to original sources

Interception-Driven Inverse Reachability for Engagement Zone Construction

In contested environments, autonomous vehicles may need to plan around adversarial pursuers whose launch locations are unknown. This paper presents an interception-driven inverse-reachability framework for inferring a feasible pursuer launch region directly from observed interception events for a single pursuer. Each interception induces a geometric constraint on the unknown launch location, and intersecting these constraints yields a bounded set guaranteed to contain the true origin under maximum-capability assumptions. Mapping this inferred set through the pursuer reachable region produces deterministic engagement zones with an explicit worst-case safety interpretation. A probabilistic extension models uncertainty in the pursuer launch location and yields graded engagement-risk fields for risk-aware planning. To accelerate localization, we introduce an information-driven planner for sacrificial agents that selects trajectories to maximize expected contraction of the feasible launch region. Monte Carlo simulations show that the proposed framework rapidly reduces launch-location uncertainty and enables substantially shorter safe trajectories after only a small number of sacrificial deployments.

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Safe Navigation in the Presence of Range-Limited Pursuers

This paper examines the degree to which an evader seeking a safe and efficient path to a target location can benefit from increasing levels of knowledge regarding one or more range-limited pursuers seeking to intercept it. Unlike previous work, this research considers the time of flight of the pursuers actively attempting interception. It is shown that additional knowledge allows the evader to safely steer closer to the threats, shortening paths without accepting additional risk of capture. A control heuristic is presented, suitable for real-time implementation, which capitalizes on all knowledge available to the evader.

math.OC

Reactive Vehicle Guidance using Dynamic Maneuvering Cue

Recent approaches for navigating among dynamic threat regions (i.e., weapon engagement zones) have focused on planning entire trajectories. Moreover, the allowance for penetration into these threat regions was based on heuristic measurements of risk. This paper offers an approach for a more reactive (i.e., feedback-based) guidance that is based on closed-form analytical expressions and thereby suitable for onboard, real-time execution. In addition, a risk measurement is formulated based upon the concept of Dynamic Maneuvering Cue (DMC) which measures the amount of turn a vehicle would need to take in its current state in order to put itself outside the threat region. This approach is then extended to handle multiple threat regions simultaneously (with minimal additional computational complexity). Finally, the DMC constraint is applied to a simple feedback controller as well as a model predictive controller (MPC). The MPC shows better performance but at the cost of having to solve an optimization problem online versus the meager computational burden associated with the simple controller. This approach, which is based on assuming the threats are adversarial, may be used as a conservative method for collision avoidance and deconfliction.

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Target Defense Using a Turret and Mobile Defender Team

A scenario is considered wherein a stationary, turn constrained agent (Turret) and a mobile agent (Defender) cooperate to protect the former from an adversarial mobile agent (Attacker). The Attacker wishes to reach the Turret prior to getting captured by either the Defender or Turret, if possible. Meanwhile, the Defender and Turret seek to capture the Attacker as far from the Turret as possible. This scenario is formulated as a differential game and solved using a geometric approach. Necessary and sufficient conditions for the Turret-Defender team winning and the Attacker winning are given. In the case of the Turret-Defender team winning equilibrium strategies for the min max terminal distance of the Attacker to the Turret are given. Three cases arise corresponding to solo capture by the Defender, solo capture by the Turret, and capture simultaneously by both Turret and Defender.

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Mutual Support by Sensor-Attacker Team for a Passive Target

We introduce a pursuit game played between a team of a sensor and an attacker and a mobile target in the unbounded Euclidean plane. The target is faster than the sensor, but slower than the attacker. The sensor's objective is to keep the target within a sensing radius so that the attacker can capture the target, whereas the target seeks to escape by reaching beyond the sensing radius from the sensor without getting captured by the attacker. We assume that as long as the target is within the sensing radius from the sensor, the sensor-attacker team is able to measure the target's instantaneous position and velocity. We pose and solve this problem as a \emph{game of kind} in which the target uses an open-loop strategy (passive target). Aside from the novel formulation, our contributions are four-fold. First, we present optimal strategies for both the sensor and the attacker, according to their respective objectives. Specifically, we design a sensor strategy that maximizes the duration for which the target remains within its sensing range, while the attacker uses proportional navigation to capture the target. Second, we characterize the \emph{sensable region} -- the region in the plane in which the target remains within the sensing radius of the sensor during the game -- and show that capture is guaranteed {if and only if} the Apollonius circle between the attacker and the target is fully contained within this region. Third, we {derive a lower bound} on the target's speed below which capture is guaranteed, and an upper bound on the target speed above which there exists an escape strategy for the target, from an arbitrary initial orientation between the agents. Fourth, for a given initial orientation between the agents, we present a sharper upper bound on the target speed above which there exists an escape strategy for the target.

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Operator-Theoretic Methods for Differential Games

Differential game theory offers an approach for modeling interactions between two or more agents that occur in continuous time. The goal of each agent is to optimize its objective cost functional. In this paper, we present two different methods, based on the Koopman Operator (KO), to solve a zero-sum differential game. The first approach uses the resolvent of the KO to calculate a continuous-time global feedback solution over the entire domain. The second approach uses a discrete-time, data-driven KO representation with control to calculate open-loop control policies one trajectory at a time. We demonstrate these methods on a turret defense game from the literature, and we find that the methods' solutions replicate the behavior of the analytical solution provided in the literature.. Following that demonstration, we highlight the relative advantages and disadvantages of each method and discuss potential future work for this line of research.

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One-vs-one Threat-Aware Weaponeering with Basic Engagement Zones

In this paper we address the problem of 'weaponeering', i.e., placing the weapon engagement zone (WEZ) of a vehicle on a moving target, while simultaneously avoiding the target's WEZ. A WEZ describes the lethality region of a range-limited weapon considering both the range of the weapon along with the state of the target. The weapons are assumed to have simple motion, while the vehicles carrying the weapons are modeled with Dubins dynamics. Three scenarios are investigated and are differentiated in the assumptions that can be made about the target in the process of the vehicle control design: 1) no knowledge of target control, 2) avoid unsafe positions assuming the target's optimal control, 3) full knowledge of target's optimal control. The engagement is formulated as a stochastic optimal control problem with uncertainty in the target's control modeled using a noise parameter applied to the target's control input. After discretizing the Hamilton-Jacobi-Bellman equation, Value iteration is then used to obtain an approximate solution for the optimal vehicle control and time-to-go. Simulation results support usage of the first paradigm: assume no knowledge of the target's control.

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Engagement Zones for a Turn Constrained Pursuer

This work derives two basic engagement zone models, describing regions of potential risk or capture for a mobile vehicle by a pursuer. The pursuer is modeled as having turn-constraints rather than simple motion. Turn-only (C-Paths) and turn-straight (CS-Paths) paths are considered for the pursuer of limited range. Following the derivation, a simulation of a vehicle avoiding the pursuer's engagement zone is provided.

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Min-Time Escape of a Dubins Car from a Polygon

A turn constrained vehicle is initially located inside a polygon region and desires to escape in minimum time. First, the method of characteristics is used to describe the time-optimal strategies for reaching a line of infinite length. Next, the approach is extended to polygons constructed of a series of line segments. Using this construction technique, the min-time path to reach each edge is obtained; the resulting minimum of the set of optimal trajectories is then selected for escaping the polygon.

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Deception in Differential Games: Information Limiting Strategy to Induce Dilemma

Can deception exist in differential games? We provide a case study for a Turret-Attacker differential game, where two Attackers seek to score points by reaching a target region while a Turret tries to minimize the score by aligning itself with the Attackers before they reach the target. In contrast to the original problem solved with complete information, we assume that the Turret only has partial information about the maximum speed of the Attackers. We investigate whether there is any incentive for the Attackers to move slower than their maximum speed in order to ``deceive'' the Turret into taking suboptimal actions. We first describe the existence of a dilemma that the Turret may face. Then we derive a set of initial conditions from which the Attackers can force the Turret into a situation where it must take a guess.

cs.GT

Linear Quadratic Guidance Law for Joint Motion Planning of a Pursuer-Turret Assembly

This paper presents joint motion planning of a vehicle with an attached rotating turret. The turret has a limited range as well as the field of view. The objective is capture a maneuvering target such that at the terminal time it is withing the field-of-view and range limits. Catering to it, we present a minimum effort guidance law that commensurate for the turn rate abilities of the vehicle and the turret. The guidance law is obtained using linearization about the collision triangle and admits an analytical solution. Simulation results are presented to exemplify the cooperation between the turret and the vehicle.

cs.RO

Pursuit-Evasion on a Sphere and When It Can Be Considered Flat

In classical works on a planar differential pursuit-evasion game with a faster pursuer, the intercept point resulting from the equilibrium strategies lies on the Apollonius circle. This property was exploited for the construction of the equilibrium strategies for two faster pursuers against one evader. Extensions for planar multiple-pursuer single-evader scenarios have been considered. We study a pursuit-evasion game on a sphere and the relation of the equilibrium intercept point to the Apollonius domain on the sphere. The domain is a generalization of the planar Apollonius circle set. We find a condition resulting in the intercept point belonging to the Apollonius domain, which is the characteristic of the planar game solution. Finally, we use this characteristic to discuss pursuit and evasion strategies in the context of two pursuers and a single slower evader on the sphere and illustrate it using numerical simulations.

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Shortest Trajectory of a Dubins Vehicle with a Controllable Laser

We formulate a novel planar motion planning problem for a Dubins-Laser system that consists of a Dubins vehicle with an attached controllable laser. The vehicle moves with unit speed and the laser, having a finite range, can rotate in a clockwise or anti-clockwise direction with a bounded angular rate. From an arbitrary initial position and orientation, the objective is to steer the system so that a given static target is within the range of the laser and the laser is oriented at it in minimum time. We characterize multiple properties of the optimal trajectory and establish that the optimal trajectory for the Dubins-laser system is one out of a total of 16 candidates. Finally, we provide numerical insights that illustrate the properties characterized in this work.

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Sampling-Based Risk-Aware Path Planning Around Dynamic Engagement Zones

Existing methods for avoiding dynamic engagement zones (EZs) and minimizing risk leverage the calculus of variations to obtain optimal paths. While such methods are deterministic, they scale poorly as the number of engagement zones increases. Furthermore, optimal-control based strategies are sensitive to initial guesses and often converge to local, rather than global, minima. This paper presents a novel sampling-based approach to obtain a feasible flight plan for a Dubins vehicle to reach a desired location in a bounded operating region in the presence of a large number of engagement zones. The dynamic EZs are coupled to the vehicle dynamics through its heading angle. Thus, the dynamic two-dimensional obstacles in the (x,y) plane can be transformed into three-dimensional static obstacles in a lifted (x,y,ψ) space. This insight is leveraged in the formulation of a Rapidly-exploring Random Tree (RRT*) algorithm. The algorithm is evaluated with a Monte Carlo experiment that randomizes EZ locations to characterize the success rate and average path length as a function of the number of EZs and as the computation time made available to the planner is increased.

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Complete Solution of the Lady in the Lake Scenario

In the Lady in the Lake scenario, a mobile agent, L, is pitted against an agent, M, who is constrained to move along the perimeter of a circle. L is assumed to begin inside the circle and wishes to escape to the perimeter with some finite angular separation from M at the perimeter. This scenario has, in the past, been formulated as a zero-sum differential game wherein L seeks to maximize terminal separation and M seeks to minimize it. Its solution is well-known. However, there is a large portion of the state space for which the canonical solution does not yield a unique equilibrium strategy. This paper provides such a unique strategy by solving an auxiliary zero-sum differential game. In the auxiliary differential game, L seeks to reach a point opposite of M at a radius for which their maximum angular speeds are equal (i.e., the antipodal point). L wishes to minimize the time to reach this point while M wishes to maximize it. The solution of the auxiliary differential game is comprised of a Focal Line, a Universal Line, and their tributaries. The Focal Line tributaries' equilibrium strategy for L is semi-analytic, while the Universal Line tributaries' equilibrium strategy is obtained in closed form.

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Optimal Evasion from a Sensing-Limited Pursuer

This paper investigates a partial-information pursuit evasion game in which the Pursuer has a limited-range sensor to detect the Evader. Given a fixed final time, we derive the optimal evasion strategy for the Evader to maximize its distance from the pursuer at the end. Our analysis reveals that in certain parametric regimes, the optimal Evasion strategy involves a 'risky' maneuver, where the Evader's trajectory comes extremely close to the pursuer's sensing boundary before moving behind the Pursuer. Additionally, we explore a special case in which the Pursuer can choose the final time. In this scenario, we determine a (Nash) equilibrium pair for both the final time and the evasion strategy.

cs.GT

Virtual Target Selection for a Multiple-Pursuer Multiple-Evader Scenario

This paper considers an M-pursuer N-evader scenario involving virtual targets. The virtual targets serve as an intermediary target for the pursuers, allowing the pursuers to delay their final assignment to the evaders. However, upon reaching the virtual target, the pursuers must decide which evader to capture. It is assumed that there are more pursuers than evaders and that the pursuers are faster than the evaders. The objective is two-part: first, assign each pursuer to a virtual target and evader such that the pursuer team's energy is minimized, and second, choose the virtual targets' locations for this minimization problem. The approach taken is to consider the Apollonius geometry between each pursuer's virtual target location and each evader. Using the constructed Apollonius circles, the pursuer's travel distance and maneuver at a virtual target are obtained. These metrics serve as a gauge for the total energy required to capture a particular evader and are used to solve the joint virtual target selection and pursuer-evader assignment problem. This paper provides a mathematical definition of this problem, the solution approach taken, and an example.

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