A5077738424- Guidance and Control Systems
- Adaptive Control of Nonlinear Systems
- Spacecraft Dynamics and Control
- Military Defense Systems Analysis
- Robotic Path Planning Algorithms
- Optimization and Search Problems
- Advanced Multi-Objective Optimization Algorithms
- Aerospace Engineering and Control Systems
- Target Tracking and Data Fusion in Sensor Networks
- Fault Detection and Control Systems
- Robotics and Sensor-Based Localization
- Probabilistic and Robust Engineering Design
- Advanced Bandit Algorithms Research
- Advanced Measurement and Detection Methods
- Aerospace and Aviation Technology
- Distributed Control Multi-Agent Systems
- Electromagnetic Launch and Propulsion Technology
- Space Satellite Systems and Control
- Computational Fluid Dynamics and Aerodynamics
- Control and Dynamics of Mobile Robots
- Indoor and Outdoor Localization Technologies
- Control Systems and Identification
- Inertial Sensor and Navigation
- Metaheuristic Optimization Algorithms Research
- UAV Applications and Optimization
Harbin Institute of Technology
2016-2025
Anqing Normal University
2024
Indiana University Bloomington
2019-2021
Heilongjiang Institute of Technology
2010-2020
Indiana University
2018-2019
University of Illinois Urbana-Champaign
2019
Shanghai University of Engineering Science
2016-2018
Chalmers University of Technology
2010
The optimization of quadrotors for the efficient and autonomous exploration complex, unknown environments construction corresponding maps with integrity is high priority in unmanned aerial vehicle(UAV) research. To overcome challenges inefficient incomplete map UAV exploration, this study propose EFP, an frontier-based strategy environments. For this, UFOMap algorithm was adopted to represent entire environment reduce time. Its accurate representation hierarchical frontiers structure were...
Latin hypercube design (LHD) is a multi-stratified sampling method, which has been frequently used in sampling-based analysis. To achieve good space-filling quality of LHD, an efficient termed local search-based genetic algorithm (LSGA), proposed this article for constructing optimal LHD. LSGA adopts modified order crossover, probabilistic mutation and adaptive selection operators to enrich population diversity speed up convergence. A search strategy also presented the approach enhance...
Best arm identification (or, pure exploration) in multi-armed bandits is a fundamental problem machine learning. In this paper we study the distributed version of where have multiple agents, and they want to learn best collaboratively. We quantify power collaboration under limited interaction communication steps), as expensive many settings. measure running time algorithm speedup over centralized there only one agent. give almost tight round-speedup tradeoffs for problem, along which develop...
A new type of guidance strategy, combining linear quadratic and norm-bounded game theory, is proposed for the scenario an attacker against active defense aircraft in three-player engagement. The problem involves three players, attacker, a defender target. differential theory solution Hamiltonian equation are utilized to obtain combined strategy each player with arbitrary-order dynamics. process divided into 4 phases, C1-C4, according switching time. scheme employed reduce fuel cost parts C1...
According to the characteristics of multiple missiles cooperative guidance, a time-cooperative guidance architecture based on leader-follower strategy is proposed. This composed individual for each missile and coordinating whole system. The central process unit situated at leader coordinates system, information broadcasted from followers. coordinate includes expected impact time relative motion target. has brief structure, short little hand on. For features structure follower have no seeker,...
A differential game guidance scheme with obstacle avoidance, based on the formulation of a combined linear quadratic and norm-bounded game, is designed for three-player engagement scenario, which includes pursuer, an interceptor, evader. The confrontation between players divided into four phases (P1–P4) by introducing switching time, proposing different strategies according to phase where static located: method employed devise energy optimization when located in P1 P3 stages; strategy...
In decomposition-based multi-objective evolutionary algorithms (MOEAs), the inconsistency between a problem's Pareto front shape and distribution of weights can lead to poor, unevenly distributed solution set. A straightforward way overcome this undesirable issue is adapt during process. However, existing methods, which typically many at time, may hinder convergence population since changing essentially means sub-problems be optimised. paper, we aim tackle by designing steady-state weight...