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This article presents the simulation genetic algorithms with multi-agent system application to solve problems of collaboration and coordination, with the goal of minimizing the travel time of a fleet of drones. The experimental analysis compares the travel time of a deterministic algorithm versus a probabilistic algorithm in a multi-agent system with BDI architecture. The results show that the genetic...
In this paper, a quadrotor path-planning problem while avoiding obstacles, in different shapes and sizes, is considered. The quadrotor is assumed to pass by a set of scattered points or regions defined according to the desired mission following the shortest path. The problem is solved by using a two-scale proposed algorithm. In the first scale, multi-directional optimal Rapidly-exploring Random Trees...
Two novel methods of complex surface segmentation in robot spray trajectory planning are developed. It is designed by using genetic algorithm. The first method is able to separate the largest patch from the surface, while the second approach is capable of dividing the surface with the smallest number of slices. Moreover, different initial triangles are selected to produce different segmentation results...
In this paper an optimal control method for parafoil system homing planning is introduced, which includes multi-phase homing arrangement, optimal homing path calculation using genetic algorithm(GA), and Bezier curves based path planning for parafoil terminal guidance to deal with the situation of variable glide ratios. L1 nonlinear algorithm is adopted to make trajectory tracking. Comparison simulations...
This work adopts a standard Denavit–Hartenberg method to model a PUMA 560 spot welding robot as the object of study. The forward and inverse kinematics solutions are then analyzed. To address the shortcomings of the ant colony algorithm, factors from the particle swarm optimization and the genetic algorithm are introduced into this algorithm. Subsequently, the resulting hybrid algorithm and the ant...
In order to solve the difficult problem of multi-objective planning, on the relevant introduced issue, firstly the paper describes multi-objective planning methods; then GAPS-MMA (Genetic Algorithm based Pareto Set for Multi-objective Mission-planning Algorithm) is completed, the main part of the algorithm, namely computing fitness value and updating Pareto sets, are focused on research, and the process...
Optimal trajectory planning for robot manipulators is always a hot spot in research fields of robotics. This paper presents a Constraint Immune Multi-objective Optimization Algorithm (CIMOA) for computing optimal trajectory of an industrial robot manipulator. The problem has a multi-criterion character in which two objectives, the minimum traveling time objective and minimum mechanical energy consumption...
In this paper we present a motion planning algorithm that combines between Probabilistic Roadmaps (PRM) and Hierarchical Genetic Algorithms (HGA) in order to generate optimal motions for a non holonomic mobile robot. PRM are used to generate a set of paths that will be optimized by HGA, the obtained trajectory leads a non holonomic mobile robot from an initial to a final configuration while maintaining...
According to the work features and requirements of SCARA robot, a motion trajectory is planed following the request of speed and acceleration at the starting point and termination point. The planning uses the joint spatial method based on genetic-algorithms. The objective function is the moving time and mechanical impact. The target is a high-profile on the joint angles.
Reusable launch vehicle (RLV) trajectory optimization of terminal area energy management (TAEM) phase is a multiple constrained optimal control problem. In order to achieve the RLV auto-landing window requirements, a new intelligent optimization method based on the flight corridor formed from altitude versus acceleration plane for RLV pre-final phase is presented. This research establishes three-degree-of-freedom...
In this paper, an improved differential search (DS) algorithm was proposed to solve the trajectory planning problem. The DS algorithm is a new kind of evolutionary algorithm that developes rapidly recently. However, slow convergence speed and easily trapping into local optimum of the DS algorithm are the main disadvantages that limit its further application. To overcome the disadvantages of DS algorithm,...
The paper investigates a path planning and following algorithm of observing targets for an underwater vehicle-manipulator system(UVMS). The algorithm including the operational task assignment and path following for the UVMS is proposed. The operational task assignment consists of path planning and task assignment. Path planning provides planned trajectory distance between any two targets for task...
Minimally invasive and computer-assisted interventions and surgeries are getting widely accepted by patients and clinicians due to improved clinical outcomes. The new paradigm involves more advanced medical instruments, among which Radiofrequency Ablation (RFA) is one type of intervention to kill tumor tissues using a needle-like electrode. In this paper, a computational optimization algorithm to...
This article studied on the rotation motion of trimaran unmanned surface vessel. The experiment has been based on the trimaran unmanned surface vessel model. We selected the Genetic algorithm as the optimization method first, then identified the test data of trimaran unmanned surface vessel rotation motion by the program assisted with ISIGHT-FD software. Having compared the identified results with...
In this paper, a potential-based genetic algorithm is proposed for formation control of robot swarm. The proposed algorithm consists of a global path planner and a motion planner. The global path planning algorithm searches a path, which the center of robot swarm should follow, within a Voronoi diagram of the free space. The motion planning is a genetic algorithm based on artificial potential models...
Optimal trajectory planning for robot manipulators is a very important issue in the research field of robotics. Many applications require smooth trajectories and the minimization of a performance index, usually the traveling time or the mechanical energy of the actuators. This paper presents a novel method that uses eighth-degree polynomial functions to generate smooth trajectories for the parametric...
QPSO algorithm (QPSO) is introduced to design a collision-free trajectory for planar redundant manipulators. Chaotic sequences instead of random sequences are used in QPSO to diversify the QPSO population. Kinematics redundancy is integrated into the presented method as planning variables. Quadrinomial and quintic polynomials are used to describe the segment of the trajectory. QPSO optimizes the trajectory...
To the problem of cooperative ground moving target tracking using UAVs in an urban area, a novel method is presented, which based on target state fusion estimation and prediction, as well as on-line trajectory planning. Firstly, based on active sensing, a solving framework was presented, the formal representation and system model of cooperative target tracking using a team UAVs was established; secondly,...
This paper considers the problem of automatically coordinating multiple platforms to explore an unknown environment. The goal is a planning algorithm that provides a path for each platform in such a way that the collection of platforms cooperatively sense the environment in a globally efficient manner. A collection of discrete locales of interest is assumed to be known and the platforms use these...
A novel progressive genetic algorithm is developed for motion planning of a three-limbed robot. The proposed motion planning method can be used to find a optimal joints trajectory from the initial to the final position and orientation. On the basis of the genetic algorithm a kind of variable structure genetic algorithm is proposed to solve the problem of motion planning of the three-limbed in dynamic...
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