Mobile Robots and Intelligent Environments

Author(s):  
Francesco Capezio ◽  
Fulvio Mastrogiovanni ◽  
Antonio Sgorbissa ◽  
Renato Zaccaria
2020 ◽  
Vol 32 (6) ◽  
pp. 1211-1218
Author(s):  
Tomohiro Umetani ◽  
◽  
Yuya Kondo ◽  
Takuma Tokuda

Automated mobile platforms are commonly used to provide services for people in an intelligent environment. Data on the physical position of personal electronic devices or mobile robots are important for information services and robotic applications. Therefore, automated mobile robots are required to reconstruct location data in surveillance tasks. This paper describes the development of an autonomous mobile robot to achieve tasks in intelligent environments. In particular, the robot constructed route maps in outdoor environments using laser imaging detection and ranging (LiDAR), and RGB-D sensors via simultaneous localization and mapping. The mobile robot system was developed based on a robot operating system (ROS), reusing existing software. The robot participated in the Nakanoshima Challenge, which is an experimental demonstration test of mobile robots in Osaka, Japan. The results of the experiments and outdoor field tests demonstrate the feasibility of the proposed robot system.


2012 ◽  
Vol 132 (3) ◽  
pp. 381-388
Author(s):  
Takaaki Imaizumi ◽  
Hiroyuki Murakami ◽  
Yutaka Uchimura

2006 ◽  
Vol 65 (3) ◽  
pp. 229-241
Author(s):  
S. F. Yatsun ◽  
F. K. Freire ◽  
V. S. Dyshenko ◽  
O. A. Shadrina
Keyword(s):  

2019 ◽  
Author(s):  
Abhishek Verma ◽  
Virender Ranga

Relay node placement in wireless sensor networks for constrained environment is a critical task due to various unavoidable constraints. One of the most important constraints is unpredictable obstacles. Handling obstacles during relay node placement is complicated because of complexity involved to estimate the shape and size of obstacles. This paper presents an Obstacle-resistant relay node placement strategy (ORRNP). The proposed solution not only handles the obstacles but also estimates best locations for relay node placement in the network. It also does not involve any additional hardware (mobile robots) to estimate node locations thus can significantly reduce the deployment costs. Simulation results show the effectiveness of our proposed approach.


Sign in / Sign up

Export Citation Format

Share Document