Inicio  /  Applied Sciences  /  Vol: 11 Par: 1 (2021)  /  Artículo
ARTÍCULO
TITULO

Motion Planning for Mobile Robot with Modified BIT* and MPC

Puyong Xu    
Ning Wang    
Shi-Lu Dai and Lei Zuo    

Resumen

In this paper, a mobile robot motion planning method with modified BIT* (batch informed trees) and MPC (Model Predictive Control) is presented. The conventional BIT* was modified here by integrating a stretch method that improves the path points connections, to get a collision-free path more quickly. After getting a reference path, the MPC method is employed to determine the motion at each moment with a given objective function. In the objective function, a repulsive function based on the direction and distance of the obstacles is introduced to avoid the robot being too close to the obstacle, so the safety can be ensured. Simulation results show the good navigation performance of the whole framework in different scenarios.

 Artículos similares

       
 
Rongke Wei, Haodong Pei, Dongjie Wu, Changwen Zeng, Xin Ai and Huixian Duan    
The task of 3D reconstruction of urban targets holds pivotal importance for various applications, including autonomous driving, digital twin technology, and urban planning and development. The intricate nature of urban landscapes presents substantial cha... ver más
Revista: Applied Sciences

 
Xiaonan Wang, Yang Guo and Yuan Gao    
Non-terrestrial network (NTN) is a trending topic in the field of communication, as it shows promise for scenarios in which terrestrial infrastructure is unavailable. Unmanned autonomous intelligent systems (UAISs), as a physical form of artificial intel... ver más
Revista: Information

 
Beom-Joon Park and Hyun-Joon Chung    
The growing trend of onboard computational autonomy has increased the need for self-reliant rovers (SRRs) with high efficiency for unmanned rover activities. Mobility is directly associated with a successful execution mission, thus fault response for act... ver más
Revista: Aerospace

 
Yu Han, Xiaolei Ma, Bo Wang, Hongwang Zhang, Qiuxia Zhang and Gang Chen    
Nonlinear Model Predictive Control (NMPC) is an effective approach for motion planning in autonomous vehicles that need to satisfy multiple driving demands. Within the realm of planner design, current strategies inadequately address the issues related to... ver más
Revista: Applied Sciences

 
Xi Lyu, Yushan Sun, Lifeng Wang, Jiehui Tan and Liwen Zhang    
This study aims to solve the problems of sparse reward, single policy, and poor environmental adaptability in the local motion planning task of autonomous underwater vehicles (AUVs). We propose a two-layer deep deterministic policy gradient algorithm-bas... ver más