Autonomous Reconnaissance Research Articles

Parameter calculation and analysis of autonomous reconnaissance for UAV-borne photoelectric payload

Parameter calculation and analysis of autonomous reconnaissance for UAV-borne photoelectric payload

Real-Time Segmentation of Artificial Targets Using a Dual-Modal Efficient Attention Fusion Network

The fusion of spectral–polarimetric information can improve the autonomous reconnaissance capability of unmanned aerial vehicles (UAVs) in detecting artificial targets. However, the current spectral and polarization imaging systems typically suffer from low image sampling resolution, which can lead to the loss of target information. Most existing segmentation algorithms neglect the similarities and differences between multimodal features, resulting in reduced accuracy and robustness of the algorithms. To address these challenges, a real-time spectral–polarimetric segmentation algorithm for artificial targets based on an efficient attention fusion network, called ESPFNet (efficient spectral–polarimetric fusion network) is proposed. The network employs a coordination attention bimodal fusion (CABF) module and a complex atrous spatial pyramid pooling (CASPP) module to fuse and enhance low-level and high-level features at different scales from the spectral feature images and the polarization encoded images, effectively achieving the segmentation of artificial targets. Additionally, the introduction of the residual dense block (RDB) module refines feature extraction, further enhancing the network’s ability to classify pixels. In order to test the algorithm’s performance, a spectral–polarimetric image dataset of artificial targets, named SPIAO (spectral–polarimetric image of artificial objects) is constructed, which contains various camouflaged nets and camouflaged plates with different properties. The experimental results on the SPIAO dataset demonstrate that the proposed method accurately detects the artificial targets, achieving a mean intersection-over-union (MIoU) of 80.4%, a mean pixel accuracy (MPA) of 88.1%, and a detection rate of 27.5 frames per second, meeting the real-time requirement. The research has the potential to provide a new multimodal detection technique for enabling autonomous reconnaissance by UAVs in complex scenes.

Research on Design of Photoelectric Turntable for Autonomous Reconnaissance

In this paper, the structural types of autonomous reconnaissance photoelectric turntables and the electrical system design methods of autonomous reconnaissance control are proposed and simplified. Meantime, the key technologies of autonomous reconnaissance photoelectric turntables are proposed and simplified, and the human-computer interaction interface of the autonomous reconnaissance photoelectric turntable is described, the concept of autonomous collaboration and its corresponding collaborative algorithms is explained, and the prospects for future development direction are proposed.

Autonomous Reconnaissance Trajectory Guidance at Small Near-Earth Asteroids via Reinforcement Learning

Autonomous capabilities could be an essential aspect of future near-Earth asteroid exploration missions, enabling a fleet of low-cost spacecraft to be distributed to various targets for increased scientific and engineering returns. This paper studies the design of an adaptive offline policy for a surface imaging task under the influence of maneuver noise via reinforcement learning (RL). An adaptive policy that responds to the changes in the environment is obtained by including asteroid parameters as part of the feedback state and randomizing them during the training. The proximal policy optimization algorithm is used to train the policy. The robustness of the policy is tested in an environment that has unmodeled dynamical effects. Further, the overall performance of the autonomous exploration scheme is studied by combining the RL-based policy with the previously proposed autonomous navigation strategy that is built around optical and measurements. The end-to-end simulations that combine both onboard navigation and guidance are performed using asteroid Bennu as an example target, and the results show that the proposed scheme is robust.

Operational Effectiveness Evaluation of UAV Cluster Based on Bayesian Networks

This paper focuses on the requirements of operational efficiency evaluation for UAV cluster, and establishes an evaluation index system for UAV cluster operations, and establishes evaluation index system from the aspects of cooperative attack capability, autonomous reconnaissance capability, instant messaging capability, rapid planning capability and autonomous formation capability. The evaluation network model is built by using Bayesian network, and the corresponding prior and conditional probabilities are calculated. The effectiveness values of each capability are calculated and verified by experiments. This paper provides an applicable quantitative evaluation method for UAV cluster operational effectiveness evaluation.

ПРИНЦИПИ ПОБУДОВИ ТА СКЛАДОВІ МОДЕЛІ ЗАСТОСУВАННЯ АВТОНОМНОГО РОЗВІДУВАЛЬНО-УДАРНОГО КОМПЛЕКСУ РАКЕТНИХ ВІЙСЬК І АРТИЛЕРІЇ

Based on the results of scientific research, the authors consider the structural and functional description of the reconnaissance and strike complex and identify the basic principles and components of its application in the interests of forming operational and tactical requirements for products that should be equipped with promising weapons and military equipment. The use of such complex elements of grouping troops as a reconnaissance and strike complex can be described by various models depending on the tasks of modeling and is conditioned by the requirement of the principle of target specification of models, including to justify operational and tactical requirements. The purpose of the article is to determine the basic principles of construction and components of the model of application of the reconnaissance and strike complex. Modeling of the use of an autonomous reconnaissance and strike complex is proposed to take into account the characteristic functioning of the actions of its components, which makes it possible to take into account the conditions of the military operation (actions). To take into account the complexity and diversity of processes of application of promising autonomous reconnaissance and strike systems, it is proposed to use system modeling, the essence of which is to create a model of combat operations of opposing parties on the basis of simpler partial models. According to the method of system modeling, the model of application of an autonomous reconnaissance and strike complex can be created by sequential construction of a hierarchical structure of modules, partial action models, functioning and their mutual coordination by purpose, place, time, forces, means, etc. In this regard, the development of the model involves: the formation of variable modules of the conditions of use with their subsequent composition with the development of the target environment, certain restrictions on other conditions of use; development of standard blocks of calculations (mathematical component of the model of application of reconnaissance and strike complex); application of methods of formal logic, queuing system, probability theory, parameter analysis, etc .; use of parametric relations to describe the studied processes. Keywords: application model, reconnaissance and strike complex, operational and tactical requirements, missile troops and artillery.

Collective Perception Using UAVs: Autonomous Aerial Reconnaissance in a Complex Urban Environment.

This article examines autonomous reconnaissance in a complex urban environment using unmanned aerial vehicles (UAVs). Environments with many buildings and other types of obstacles and/or an uneven terrain are harder to be explored as occlusion of objects of interest may often occur. First, in this article, the problem of autonomous reconnaissance in a complex urban environment via a swarm of UAVs is formulated. Then, the algorithm based on the metaheuristic approach is proposed for a solution. This solution lies in deploying a number of waypoints in the area of interest to be explored, from which the monitoring is performed, and planning the routes for available UAVs among these waypoints so that the monitored area is as large as possible and the operation as short as possible. In the last part of this article, two types of main experiments based on computer simulations are designed to verify the proposed algorithms. The first type focuses on comparing the results achieved on the benchmark instances with the optimal solutions. The second one presents and discusses the results obtained from a number of scenarios, which are based on typical reconnaissance operations in real environments.

자율정찰비행 무인항공기의 비행운영조건 고찰을 위한 비행시뮬레이션 개발

자율정찰비행 무인항공기의 비행운영조건 고찰을 위한 비행시뮬레이션 개발

Cooperative Path Planning for Target Tracking in Urban Environments Using Unmanned Air and Ground Vehicles

As the need for autonomous reconnaissance and surveillance missions in cluttered urban environments has been increasing, this paper describes a cooperative path planning algorithm for tracking a moving target in urban environments using both unmanned air vehicles (UAVs) and unmanned ground vehicles (UGVs). The novelty of the algorithm is that it takes into account vision occlusions due to obstacles in the environment. The algorithm uses a dynamic occupancy grid to model the target state, which is updated by sensor measurements using a Bayesian filter. Based on the current and predicted target behavior, the path planning algorithm for a single vehicle (UAV/UGV) is first designed to maximize the sum of the probability of detection over a finite look-ahead horizon. The algorithm is then extended to multiple vehicle collaboration scenarios, where a decentralized planning algorithm relying on an auction scheme is designed to plan finite look-ahead paths that maximize the sum of the joint probability of detection over all vehicles.

EFFECTS OF PROPELLER BLADE TWIST ON RECONNAISSANCE QUAD-ROTOR UAV

ABSTRACTRotors play a pivotal role in the overall performance of a rotary-wing aircraft. Forcesand moments required for flight are achieved through effective, compact and high-liftrotor design. Important rotor parameters are thrust, power and torque, which arefunctions of blade twist and rotor radius. A robust and efficient rotary-wing UAV flightcontrol system must provide the vehicle with the ability to perform safe flightmanoeuvres. This comprise normal flight conditions and proportionate regulation ofthrust in response to the variation in power demand, which comes to play due tochanges in aerodynamics conditions within the vehicle operating environment. Thispaper presents an in-depth analysis on the effect of variations of propeller blade twistand diameter with the view to designing an autonomous flight control system for amicro rotary-wing UAV. Virtual Blade Model (VBM) was used for the analysis and theresult validated using a quad-rotor vehicle. The study comes up with an efficientpropeller choice suitable for autonomous reconnaissance quad-rotor UAV.

A portable, autonomous, urban reconnaissance robot

Portable mobile robots, in the size class of 20 kg or less, could be extremely valuable as autonomous reconnaissance platforms in urban hostage situations and disaster relief. We have developed a prototype urban robot on a novel chassis with articulated tracks that enable stair climbing and scrambling over rubble. Autonomous navigation capabilities of the robot include stereo vision-based obstacle avoidance, visual servoing to user-designated goals, and autonomous vision-guided stair climbing. The system was demonstrated in an urban reconnaissance mission scenario at Fort Sam Houston in October 1999. A two-axis scanning laser rangefinder has been developed and integrated into the robot for indoor mapping and position estimation. This paper describes the robot, its performance in field trials, and some of the technical challenges that remain to enable fieldable urban reconnaissance robots.