In complex environments, path planning is the key for unmanned aerial vehicles (UAVs) to perform military missions autonomously. This paper proposes a novel algorithm called flight cost-based Rapidly-exploring Random Tree star (FC-RRT*) extending standard (RRT*) deal with safety requirements and constraints of UAVs in 3D environment. First, cost function that includes threat strength length was designed comprehensively evaluate connection between two nodes. Second, order solve UAV problem...

Abstract The real-time path planning of unmanned aerial vehicles (UAVs) in dynamic environments with moving threats is a difficult problem. To solve this problem, paper proposes time-based rapidly exploring random tree (time-based RRT*) algorithm, called the hierarchical algorithm based on potential function lazy and low-cost optimization (HPO-RRT*). HPO-RRT* can guarantee homotopy optimality high efficiency. This uses architecture comprising UAV perception system, planner, optimizer. After...

In this article, we focus on addressing the nonlinear filtering problem with unknown measurement noise covariance and outliers, which may be encountered in application strapdown inertial navigation system/global positioning system integrated system. Although existing methods, such as adaptive Kalman filter, are widely used system, their estimation accuracy is poor, paper proposes a variational Bayesian-based robust cubature filter to address problem, not only retains adaptivity when but also...

Multi-UAV cooperative path planning is a key technology to carry out multi-UAV tasks, and its research has important practical significance. A combination of single-UAV paths, so the idea problem decomposition effective deal with planning. With this analysis, algorithm based on co-evolution optimization was proposed in paper. Firstly, by analyzing meaning flight, model given. Secondly, we designed cost function multiple UAVs penalty method constraints two information-sharing strategies...

Aimed at improving upon the disadvantages of single centralized Kalman filter for integrated navigation, including its fragile robustness and low solution accuracy, a nonlinear double model based on improved decentralized federated extended (EKF) navigation is proposed. The multisensor error established simplified in this paper according to near-ground short distance applications small unmanned aerial vehicles (UAVs). In order overcome that used linear Gaussian system, EKF designed...

In this paper, a four-dimensional (4D) dynamic cooperative path planning algorithm for multiple unmanned aerial vehicles (UAVs) is proposed, in which the time variables of UAVs, as well conflict and threat avoidance, are considered. The proposed paper uses hierarchical framework that divided into 4D layer local avoidance layer. layer, algorithm, named priority rapidly exploring random trees (DPRRT*), would be used all UAVs involved given task. We first designed heuristic prioritization...

Multi-UAV cooperative path planning can improve the efficiency of task completion. To deal with space and time conflicts multi-UAVs in complex environments, a multi-collision-based multi-UAV algorithm, multi-conflict-based search (MCBS), is proposed. First, flight constraints UAV are analyzed, three-dimensional environment model established that incorporates geographical information. Then, hierarchical optimization used to design collaborative algorithms. In low-level design, combined sparse...

Aimed at improving the nonlinear integrated navigation solution performance of multiple low-cost sensors fusion, this paper presents a multilayer loosely-coupled, local-global, and step-optimized MF5DCKF (Multisensor Federated fifth-degree Cubature Kalman filter) state estimation algorithm for small unmanned aerial vehicle (UAV). This method establishes model composed attitude heading reference system (AHRS) error model, strapdown inertial system/global positioning (SINS/GPS)...

Path planning is the key technology for UAV to achieve autonomous flight. Considering shortcomings of path based on conventional potential field method, this paper proposes an improved optimization algorithm artificial method and extends it three-dimensional space better flight constrained 3D online UAVs. The optimized aiming at three problems goal nonreachable with obstacle nearby (GNWON), easy fall into local minimum, oscillation in traditional method. First, function relative distance...

This paper proposes a fast cooperative path planning algorithm for multiple UAVs that satisfies the time–space constraints, namely, RRT* based on heuristic decentralized prioritized (HDP-TSRRT*), which takes into account simultaneous arrival time variables of each UAV as well avoidance conflicts and threats. HDP-TSRRT* is hierarchical decoupling algorithm. First, all pre-paths are planned simultaneously at synchronous level. Second, coordination level, (HDP) proposed to quickly complete...

To realize unmanned aerial vehicle (UAV) situation assessment, a Bayesian network (BN) for assessment is established. Aimed at the problem that parameters of BN are difficult to obtain, an improved whale optimization algorithm based on prior parameter intervals (IWOA-PPI) learning proposed. Firstly, according dependencies between and its related factors, structure Secondly, in order fully mine knowledge parameters, constraints transformed into using Monte Carlo sampling interval...

This paper presents a model-free distributed multi-sensor extended Kalman filter (DMSEKF) full state estimation algorithm to provide long-term convergent flight parameters for small fixed-wing unmanned aerial vehicles (UAVs). The has the attitude, velocity, position, airspeed, and 2D horizontal wind speed. airspeed speed are estimated in disturbance more robust perception information. estimator low-cost standard sensor suite, including an IMU, magnetometer, barometer, GPS module, tube,...

Abstract In recent years, the multi-state constraint Kalman filter has been widely used in visual-inertial navigation of unmanned systems. However, most previous studies, measurement noise system was assumed to be Gaussian noise, but this is not case practice. paper, maximum correntropy criterion introduced into improve robustness system. First, new criterion-based introduced, it uses replace minimum mean square error suppress interference outliers on filtering results, and no numerical...

Considering the collision-prone problem near initial point, goal non-reachable with obstacle nearby (GNWON) and chattering of traditional artificial potential field algorithm(TAPF), attractive function repulsive are improved respectively, an adaptive algorithm(AAPF) is proposed. The algorithm can calculate different each path point on-line in real time. On this basis, a 2D extended to 3D space for autonomous avoidance planning quadrotor UAV. A model established, principle at nearest contact...

Aimed at the problem of small unmanned aerial vehicle (UAV) attitude solution accuracy and real-time performance in short-range navigation flight, this paper, we propose a fast weakly-coupled double-layer error-state Kalman filter (DL-ESKF) estimation algorithm. Considering application navigation, designed an improved error model for low-cost gyroscope/accelerometer/magnetometer devices. In addition, reasonably simplified certain factors that affect to reduce filtering calculation burden....

Robust and accurate state estimation algorithms applied to the small UAVs are always promising depending on multiple onboard local global sensors. This paper proposes a variational adaptive Levenberg-Marquardt iterated extended Kalman filter (VA-LM-IEKF) full algorithm calculate reliable UAV flight parameters in wind disturbance. The navigation system based LM-IEKF can provide an by expanding optimization range of estimated points. An using Bayesian approach is proposed improve robustness...

Aiming at the attitude solution accuracy and robustness for small UAVs in complex flight conditions, this paper proposes a dynamic adaptive heading systems(AHRS) estimator with singular value decomposition Cubature Kalman filter(SVDCKF). Considering problem of random bias low-cost sensor, designs method that sensor is used as state vector to eliminate effect bias. Due non-linearity AHRS model non-positive definite phenomenon covariance matrix, nonlinear filter combined designed improve...