Tsunami post disaster robot: Simulation and implementation of aerial path planning to explore unknown environment

2021 ◽  
Author(s):  
Hardefa Rizky Putu Rogonondo ◽  
Son Kuswadi ◽  
Anhar Risnumawan ◽  
Eny Kusumawati
Keyword(s):  
Path Planning ◽  
Robot Simulation ◽  
Unknown Environment ◽  
Post Disaster

Path Planning in Unknown Environment Based on Reinforcement Learning

2021 ◽  
pp. 229-236
Author(s):  
Xinshun Ning ◽  
Hongyong Yang ◽  
Zhilin Fan ◽  
Yilin Han
Keyword(s):  
Reinforcement Learning ◽  
Path Planning ◽  
Unknown Environment

scholarly journals Multi-robot informative path planning in unknown environments through continuous region partitioning

2020 ◽  
Vol 17 (6) ◽  
pp. 172988142097046
Author(s):  
Ayan Dutta ◽  
Amitabh Bhattacharya ◽  
O Patrick Kreidl ◽  
Anirban Ghosh ◽  
Prithviraj Dasgupta
Keyword(s):  
Load Balancing ◽  
Path Planning ◽  
Spatial Modeling ◽  
Hard Problem ◽  
Np Hard ◽  
Unknown Environment ◽  
Reasonable Amount ◽  
Novel Approach ◽  
Np Hard Problem ◽  
Simulation Results

We consider the NP-hard problem of multirobot informative path planning in the presence of communication constraints, where the objective is to collect higher amounts of information of an ambient phenomenon. We propose a novel approach that uses continuous region partitioning into Voronoi components to efficiently divide an initially unknown environment among the robots based on newly discovered obstacles enabling improved load balancing between robots. Simulation results show that our proposed approach is successful in reducing the initial imbalance of the robots’ allocated free regions while ensuring close-to-reality spatial modeling within a reasonable amount of time.

Sign in / Sign up

Export Citation Format

Share Document