A receding horizon control approach to obstacle avoidance

Author(s):  
Domokos Kiss ◽  
Gabor Tevesz
2016 ◽  
Vol 13 (2) ◽  
pp. 463-478 ◽  
Author(s):  
Fei Miao ◽  
Shuo Han ◽  
Shan Lin ◽  
John A. Stankovic ◽  
Desheng Zhang ◽  
...  

2022 ◽  
Vol 2 ◽  
Author(s):  
Xiaohu Zhao ◽  
Yuanyuan Zou ◽  
Shaoyuan Li

This paper investigates the multi-agent persistent monitoring problem via a novel distributed submodular receding horizon control approach. In order to approximate global monitoring performance, with the definition of sub-modularity, the original persistent monitoring objective is divided into several local objectives in a receding horizon framework, and the optimal trajectories of each agent are obtained by taking into account the neighborhood information. Specifically, the optimization horizon of each local objective is derived from the local target states and the information received from their neighboring agents. Based on the sub-modularity of each local objective, the distributed greedy algorithm is proposed. As a result, each agent coordinates with neighboring agents asynchronously and optimizes its trajectory independently, which reduces the computational complexity while achieving the global performance as much as possible. The conditions are established to ensure the estimation error converges to a bounded global performance. Finally, simulation results show the effectiveness of the proposed method.


2019 ◽  
Vol 39 (3) ◽  
pp. 445-459 ◽  
Author(s):  
Dilong Chen ◽  
Qiang Lu ◽  
Dongliang Peng ◽  
Ke Yin ◽  
Chaoliang Zhong ◽  
...  

PurposeThe purpose of this paper is to propose a receding horizon control approach for the problem of locating unknown wireless sensor networks by using a mobile robot.Design/methodology/approachA control framework is used and consists of two levels: one is a decision level, while the other is a control level. In the decision level, a spatiotemporal probability occupancy grid method is used to give the possible positions of all nodes in sensor networks, where the posterior probability distributions of sensor nodes are estimated by capturing the transient signals. In the control level, a virtual robot is designed to move along the edge of obstacles such that the problem of obstacle avoidance can be transformed into a coordination problem of multiple robots. On the basis of the possible positions of sensor nodes and virtual robots, a receding horizon control approach is proposed to control mobile robots to locate sensor nodes, where a temporary target position method is utilized to avoid several special obstacles.FindingsWhen the number of obstacles increases, the average localization errors between the actual locations and the estimated locations significantly increase.Originality/valueThe proposed control approach can guide the mobile robot to avoid obstacles and deal with the corresponding dynamical events so as to locate all sensor nodes for an unknown wireless network.


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