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Distributed game strategy 1

Distributed model predictive control (MPC) 1

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Levy flight based pigeon inspired optimization (LFPIO) 1

Non-singular fast terminal sliding mode observer (NFTSMO) 1

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Pedestrian 1

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Multi-UAV obstacle avoidance control via multi-objective social learning pigeon-inspired optimization Research

Wan-ying Ruan, Hai-bin Duan,wyruan@buaa.edu.cn,hbduan@buaa.edu.cn

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 5,   Pages 649-808 doi: 10.1631/FITEE.2000066

Abstract: We propose multi-objective social learning (MSLPIO) and apply it to for formation. In the algorithm, each pigeon learns from the better pigeon but not necessarily the global best one in the update process. A social learning factor is added to the map and compass operator and the landmark operator. In addition, a dimension-dependent parameter setting method is adopted to improve the blindness of parameter setting. We simulate the flight process of five UAVs in a complex obstacle environment. Results verify the effectiveness of the proposed method. MSLPIO has better convergence performance compared with the improved multi-objective and the improved non-dominated sorting genetic algorithm.

Keywords： 无人机；避障；鸽群优化；多目标社会学习鸽群优化    

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Distributed game strategy for unmanned aerial vehicle formation with external disturbances and obstacles Research Article

Yang YUAN, Yimin DENG, Sida LUO, Haibin DUAN

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 7,   Pages 1020-1031 doi: 10.1631/FITEE.2100559

Abstract: We investigate a for formations with external disturbances and obstacles. The strategy is based on a framework and . First, we propose a to estimate the influence of a disturbance, and prove that the observer converges in fixed time using a Lyapunov function. Second, we design an based on topology reconstruction, by which the UAV can save energy and safely pass obstacles. Third, we establish a distributed MPC framework where each UAV exchanges messages only with its neighbors. Further, the cost function of each UAV is designed, by which the UAV formation problem is transformed into a game problem. Finally, we develop LFPIO and use it to solve the Nash equilibrium. Numerical simulations are conducted, and the efficiency of LFPIO based distributed MPC is verified through comparative simulations.

Keywords： Distributed game strategy     Unmanned aerial vehicle (UAV)     Distributed model predictive control (MPC)     Levy flight based pigeon inspired optimization (LFPIO)     Non-singular fast terminal sliding mode observer (NFTSMO)     Obstacle avoidance strategy    

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An Intelligent System for Navigation Collision Prevention

Hao Yanling,Liu Yuhong,Sun Feng,Sun Yao

Strategic Study of CAE 2000, Volume 2, Issue 3,   Pages 48-53

Abstract:

The purpose of this thesis is to developing and exploiting an intelligent system for collision prevention, namely “Intelligent Collision Prevention Expert System for Navigation”(NICPES). The NICPES has a multi-unit and layering Knowledge Base systematic structure and a multi-unit Knowledge Representation (KR) which based on frame KR, production rule KR, procedure KR and neural network KR, to represent and store all kinds of knowledge for navigation collision prevention. The NICPES also builds a multi-inference system, which based on analogy inference, forward illation inference, conversion inference, neural network inference and meta-rule inference, to overcome the shortcoming of unitary inference. For-some problems in collision prevention region, the NICPES builds a set of models to solve them. These models comprise the models of judging collision risk, the model of determining collision prevention time and the model of classifying encounter situation. For multi-ship encounter situation, the NICPES puts forward a tactics to choose optimal collision prevention scheme based on Analytic Hierarchy Process (AHP) and builds a mathematical model that will be used to determine the optimal angle and sailing time during ship's turning for multi and single ship encounter situation. The simulation experiments show that the NICPES can analyze and judge various sailing cases and encounter situation ,and offer a reasonable scheme, which settle the collision problem effectively and ensure the sailing safety.

Keywords： collision prevention     expert system     neural network     fuzzy technique     multi-target optimizing    

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Stochastic pedestrian avoidance for autonomous vehicles using hybrid reinforcement learning Research Article

Huiqian LI, Jin HUANG, Zhong CAO, Diange YANG, Zhihua ZHONG,lihq20@mails.tsinghua.edu.cn,huangjin@tsinghua.edu.cn,caoc15@mails.tsinghua.edu.cn,ydg@tsinghua.edu.cn

Frontiers of Information Technology & Electronic Engineering 2023, Volume 24, Issue 1,   Pages 131-140 doi: 10.1631/FITEE.2200128

Abstract: Ensuring the safety of s is essential and challenging when are involved. Classical avoidance strategies cannot handle uncertainty, and learning-based methods lack performance guarantees. In this paper we propose a (HRL) approach for to safely interact with s behaving uncertainly. The method integrates the rule-based strategy and reinforcement learning strategy. The confidence of both strategies is evaluated using the data recorded in the training process. Then we design an activation function to select the final policy with higher confidence. In this way, we can guarantee that the final policy performance is not worse than that of the rule-based policy. To demonstrate the effectiveness of the proposed method, we validate it in simulation using an accelerated testing technique to generate stochastic s. The results indicate that it increases the success rate for avoidance to 98.8%, compared with 94.4% of the baseline method.

Keywords： Pedestrian     Hybrid reinforcement learning     Autonomous vehicles     Decision-making    

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Title Author Date Type Operation

Multi-UAV obstacle avoidance control via multi-objective social learning pigeon-inspired optimization

Wan-ying Ruan, Hai-bin Duan,wyruan@buaa.edu.cn,hbduan@buaa.edu.cn

Journal Article

Distributed game strategy for unmanned aerial vehicle formation with external disturbances and obstacles

Yang YUAN, Yimin DENG, Sida LUO, Haibin DUAN

Journal Article

An Intelligent System for Navigation Collision Prevention

Hao Yanling,Liu Yuhong,Sun Feng,Sun Yao

Journal Article

Stochastic pedestrian avoidance for autonomous vehicles using hybrid reinforcement learning

Huiqian LI, Jin HUANG, Zhong CAO, Diange YANG, Zhihua ZHONG,lihq20@mails.tsinghua.edu.cn,huangjin@tsinghua.edu.cn,caoc15@mails.tsinghua.edu.cn,ydg@tsinghua.edu.cn

Journal Article