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Hybrid Navigation Method for Multiple Robots Facing dynamic obstacles

Tsinghua Science and Technology 2022年第6期27卷 894-901页

作者： Kaidong Zhao Li Ning Shenzhen Institutes of Advanced Technology Chinese Academy of SciencesShenzhen 518055China University of Chinese Academy of Sciences Beijing 100049China

With the continuous development of robotics and artificial intelligence,robots are being increasingly used in various *** traditional navigation algorithms,such as Dijkstra and A*,many dynamic scenarios in life are difficult to cope *** solve the navigation problem of complex dynamic scenes,we present an improved reinforcement-learning-based algorithm for local path planning that allows it to perform well even when more dynamic obstacles are *** method applies the gmapping algorithm as the upper layer input and uses reinforcement learning methods as the *** algorithm enhances the robots’ability to actively avoid obstacles while retaining the adaptability of traditional methods.

关键词： simultaneous localization and mapping(SLAM) reinforcement learning multirobots dynamic obstacles robot operating system(ROS) navigation

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Optimal Path Planning of Two-Wheeled Mobile Robots in the Presence of dynamic obstacles

Optimal Path Planning of Two-Wheeled Mobile Robots in the Pr...

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第36届中国控制会议

作者： Xinwei Wang Haijun Peng Dianheng Jiang Sheng Zhang Department of Engineering Mechanics Faculty of Vehicle Engineering and MechanicsState Key Laboratory of Structural Analysis for Industrial EquipmentDalian University of Technology

ISBN: (纸本)9781538629185

To solve the problem of optimal path planning of two-wheeled mobile robots（TWMRs） in the presence of dynamic obstacles, a symplectic pseudospectral method for solving nonlinear optimal control problems with inequality constraints is developed. The proposed algorithm transforms the original nonlinear optimal problem into a series of linear-quadratic optimal control problems（LQOCPs） by using quasilinearization techniques. And the LQOCP in each iteration is replaced by a coupling of a system of linear algebraic equations and a linear complementarity problem（LCP） with the help of the parametric variational principle and the second kind of generating function. The proposed method satisfies the first-order necessary conditions for optimal control problems and matrices involved are found to be sparse and symmetric, leading it to be accurate and efficient. Numerical simulations demonstrate that the proposed method is effective for nonlinear optimal control problems with complicated constraints.

关键词： Two-wheeled mobile robot dynamic obstacles nonlinear optimal control parametric variational principle symplectic pseudospectral method

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Path Planning of Quadrotors in a dynamic Environment Using a Multicriteria Multi-Verse Optimizer

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Computers, Materials & Continua 2021年第11期69卷 2159-2180页

作者： Raja Jarray Mujahed Al-Dhaifallah Hegazy Rezk Soufiene Bouallègue Research Laboratory in Automatic Control(LARA) National Engineering School of Tunis(ENIT)University of Tunis El ManarTunis1002Tunisia Department of Systems Engineering King Fahd University of Petroleum&MineralsDhahran31261Saudi Arabia College of Engineering at Wadi Addawaser Prince Sattam Bin Abdulaziz UniversityAl-Kharj11911Saudi Arabia Department of Electrical Engineering Faculty of EngineeringMinia UniversityMinia61517Egypt High Institute of Industrial Systems of Gabès(ISSIG) University of GabèsGabès6011Tunisia

Paths planning of Unmanned Aerial Vehicles(UAVs)in a dynamic environment is considered a challenging task in autonomous flight control *** this work,an efficient method based on a Multi-Objective MultiVerse Optimization(MOMVO)algorithm is proposed and successfully applied to solve the path planning problem of quadrotors with moving *** a path planning task is formulated as a multicriteria optimization problem under operational *** proposed MOMVO-based planning approach aims to lead the drone to traverse the shortest path from the starting point and the target without collision with moving *** vehicle moves to the next position from its current one such that the line joining minimizes the total path length and allows aligning its direction towards the *** choose the best compromise solution among all the non-dominated Pareto ones obtained for compromise objectives,the modified Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)is investigated.A set of homologous metaheuristics such as Multiobjective Salp Swarm Algorithm(MSSA),Multi-Objective Grey Wolf Optimizer(MOGWO),Multi-Objective Particle Swarm Optimization(MOPSO),and Non-Dominated Genetic Algorithm II(NSGAII)is used as a basis for the performance *** results and statistical analyses show the superiority and effectiveness of the proposed MOMVO-based planning *** obtained results are satisfactory and encouraging for future practical implementation of the path planning strategy.

关键词： Quadrotors path planning dynamic obstacles multi-objective optimization global metaheuristics TOPSIS decision-making Friedman statistical tests

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Study of the Interception Scheme Based on A* Path Finding Algorithm in Computer Game

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Journal of Computer and Communications 2020年第7期8卷 32-49页

作者： Zhenjie Li Haiming Li Department of Computer Science and Technology Shanghai University of Electric Power Shanghai China

In the game, we generally use A* algorithm for pathfinding according to the target location and map information to realize the tracking and interception task. This approach is simple to implement, but is often less than ideal in its presentation, because it does not allow game units to predictably choose paths based on dynamic targets or obstacles, and may lead to blocked channels or difficulty in choosing the actual optimal path. This paper focuses on analyzing the need of a unit when intercepting another unit in the game, and make an interception scheme which can adapt itself to dynamic obstacles and moving target thus presents artificial intelligence to some extent.

关键词： Interception Path A* Algorithm dynamic obstacles dynamic A* Algorithm

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