Ketula Patel

Optimization of Weapon–Target Pairings Based on Kill Probabilities

In this paper, we present a novel optimization algorithm for assigning weapons to targets based on desired kill probabilities. For the given weapons, targets, and desired kill probabilities, our optimization algorithm assigns weapons to targets that satisfy the desired kill probabilities and minimize the overkill. The minimization of overkill assures that any proper subset of the weapons assigned to a target results in a kill probability that is less than the desired kill probability on such a target. Computational results for up to 120 weapons and 120 targets indicate that the performance of this algorithm yields an average improvement in quality of solutions of 26.8% over the greedy algorithms, whereas execution times remained on the order of milliseconds.

Effect-based weapon-target assignment with minimised collateral damage

We present an advanced algorithm that assigns weapons to targets in such a way that the desired given effects are satisfied with minimal overkill (i.e., minimal excess beyond the desired effects) and minimal collateral damage. The most obvious and natural effects on targets are represented by kill probabilities or percentages of damage these targets. Hence, our algorithm optimises weapon-target assignments with respect to the given desired effects by minimising overkill and minimising collateral damage. Our computation results included in this paper suggest that the benefit gain of decreased collateral damage obtained by our algorithm decisively overcompensates the loss/sacrificed benefit of optimised assignment related to overkill.

Semi-Autonomous Collaborative Control of Multi-Robotic Systems for Multi-Task Multi-Target Pairing

In many applications, it is required that heterogeneous multi-robots are grouped to work on multi-targets simultaneously. Therefore, this paper proposes a control method for a single-master multi-slave (SMMS) teleoperator to cooperatively control a team of mobile robots for a multi-target mission. The major components of the proposed control method are the compensation for contact forces, modified potential field based leader-follower formation, and robot-task-target pairing method. The robot-task-target paring method is derived from the proven auction algorithm for a single target and is extended for multi-robot multi-target cases, which optimizes effect-based robot-task-target pairs based on heuristic and sensory data. The robot-task-target pairing method can produce a weighted attack guidance table (WAGT), which contains benefits of different robot-task-target pairs. With the robot-task-target pairing method, subteams are formed by paired robots. The subteams perform their own paired tasks on assigned targets in the modified potential field based leader-follower formation while avoiding sensed obstacles. Simulation studies illustrate system efficacy with the proposed control method.© 2011 ASME

Network Centric Multiple Manned/Unmanned Systems (UMS) Navigation and Control Coordination

Armed unmanned systems (UMS) are beginning to be fielded in the current battlespace, and extremely common in the Future Force Battlespace. One of the major concerns of UMS development is the evolution from human intervention to Robot autonomy/intelligence. The system autonomy has been evaluated by a spectrum of measures from obstacle detection/avoidance, route planning to mission planning, pattern recognition and situation awareness. Many system level issues pertaining to collaborative behavior and swarm intelligence need to be investigated. Recently the US Army Armaments Research, Development and Engineering Center (ARDEC), developed the concept of a joint manned-unmanned system team (JMUST), for which target handoff and sharing of situational awareness (SA) data between humans and UMS working together have been demonstrated. This is a ground- breaking program in terms of implementation of advanced concepts for human-UMS teaming in combat operations, which currently has no parallel in either the Future Combat System (FCS) or Future Force Warrior (FFW) programs. With the ARDEC Combat Decision Aids System (CDAS) software system and digital UHF radios providing the network backbone, both UMS and human acquired target and SA data have been shared to all squad level assets. As a demonstration UMS platform for network centricity this paper presents personnel/platform tracking, navigation and communication system as an essential part for FCS, FFW, Objective Force Warrior, Land Warrior and Homeland Defense applications where one urgently needs to have novel position/location tracking, communications system and decision making devices that would permit multi-tracking, reporting and recording operations. This Intelligent Precision Geolocation and Control Networked Multiple UMS Demonstration system provides precision interruption-free position for multiple tracking of UMS and other combat platforms, in complicated environments and terrains. The system integrated with CDAS is realized by using the coremicro Palm Navigators with wireless ad hoc networks to perform communications and wireless location at the same time, with improved geolocation accuracy, and increased tracking area coverage. A suite of information multi-sensor fusion and wireless communications was demonstrated. The system demonstration of the fully-functional toolsets for robotics, robotic autonomy, robotic human interface, remote targeting and surveillance is presented in fusion algorithms based on the integration configuration of this paper. In recent testing the non-magnetic CPN walker unit, with the coremicro 4D GIS and CDAS with the indoor floor map of a large building was accurate as expected for indoor tracking. The maximum tracking loop in the building had a 1 to 2 meters position error.

Real-Time Targeting and Trajectory Estimation for Enhanced Network Centricity

It is envisioned that the real time collaboration and dynamic re-planning for target engagement would take place autonomously between unmanned systems (UMS) based on pre-mission planning profiles generated prior to mission initiation, with final decision on target engagement being left to the human operator. This leads directly to the need for the systems to be able to operate autonomously for extended periods, and also to be able to collaboratively engage hostile targets within specified rules of engagement. All assets are able to share a COP (common operating picture) of the battlespace and communicate sensor and target data in real time thus allowing for human or UMS target acquisition and location, transmission of the target to a weapon-target pairing system, and automated assignment of the target to a human or UMS asset as best suited. The collaborative engagement capability is developed as a distributed hardware/software processing component or components capable of insertion into multiple software architectures, and capable of use in multiple operating systems, to include real time embedded operating systems interfaced with on-board sensor, controller subsystems. This paper considers an automated target tracking, pointing and trajectory estimation system that includes components related to target acquisition, target coordinates determination, targeting information visualization and evaluation/simulation testing. Collaboration Engagement involves the target being acquired first by the Coremicro 4D GIS targeting system. Then, the real-time projectile trajectory is determined by the automated stabilization and pointing control system.

4D Geographical Information System (GIS)-Based Tracking, Prediction and Visualization of Ground Moving Targets

[Abstract]Current targeting systems such as AFATDS (Advanced Field Artillery Tactical Data System) do not have the ability to predict future locations of moving targets being tracked within the Common Operating Picture (COP). Although these systems can perform some limited terrain and mobility analysis calculations that are static in nature, they do not address the key issue of how to apply terrain and mobility factors to attack a moving target. The objective of this paper is to introduce a targeting system that investigates and demonstrates the feasibility of 4D Geographical Information System (GIS)-based tracking, prediction and visualization of ground moving targets. The system uses 3D GIS to provide a virtual 4D scenario of ground moving targets’ tracking, prediction and possible hitting point within the COP. The system utilizes new advanced technology, 3D GIS and virtual reality for tracking, prediction and 4D animation simulation of moving targets. The system consists of two parts: (1) terrain-/ mobility-based tracking and prediction of ground moving targets and (2) the visualization and 4D motion simulation.