RSSI-based mobile robot navigation in grid-pattern wireless sensor network

2013 ◽  
Author(s):  
Nan Zhou ◽  
Xiaoguang Zhao ◽  
Min Tan
Keyword(s):  
Wireless Sensor Network ◽  
Mobile Robot ◽  
Sensor Network ◽  
Robot Navigation ◽  
Wireless Sensor ◽  
Mobile Robot Navigation ◽  
Grid Pattern

scholarly journals Wireless Sensor Network and RFID Fusion Approach for Mobile Robot Navigation

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Guillermo Enriquez ◽  
Sunhong Park ◽  
Shuji Hashimoto
Keyword(s):  
Wireless Sensor Network ◽  
Mobile Robot ◽  
Radio Frequency ◽  
Sensor Network ◽  
Radio Frequency Identification ◽  
Wireless Sensor ◽  
Mobile Robot Navigation ◽  
Movement Speed ◽  
Identification System ◽  
Frequency Identification

There are numerous applications for mobile robots that require relatively high levels of speed and precision. For many systems, these two properties are a tradeoff, as oftentimes increasing the movement speed can mean failing to detect some sensors. This research attempts to create a useful and practical system by combining a wireless sensor network with a passive radio frequency identification system. The sensor network provides fast general navigation in open areas and the radio frequency identification system provides precision navigation near static obstacles. By fusing the data from both systems, we are able to provide fast and accurate navigation for a mobile robot. Additionally, with WSN nodes and passive RFID tag mats, the system infrastructure can be easily installed in existing environments.

Study on Navigation of Wireless Sensor Network Mobile Robot

2012 ◽  
Vol 591-593 ◽  
pp. 1682-1686
Author(s):  
Cang Rong Zhao ◽  
Miao Miao Zheng
Keyword(s):  
Wireless Sensor Network ◽  
Mobile Robot ◽  
Real Time ◽  
Sensor Network ◽  
Potential Field ◽  
Control Method ◽  
Wireless Sensor ◽  
Artificial Potential Field ◽  
Planning Problem ◽  
Localization Algorithm

For optimal design of mobile robot path planning problem, an improved artificial potential field control method is designed. Using infrared sensors and ultrasonic sensors to detect the surrounding environment will get the information of obstacles and goals. Proposed an adaptive real-time localization algorithm based on improved DV-Hop algorithm to realize real-time localization for wireless sensor network mobile robot. The improved artificial potential field adopted the improved potential function that ensured the goal is the global minimum so the mobile robot can reach the goal freely. The effectiveness and feasibility of the improved algorithm verified by simulation.

DESIGN AND IMPLEMENTATION OF WIRELESS SENSOR NETWORK FOR ROBOT NAVIGATION

2007 ◽  
Vol 04 (01) ◽  
pp. 77-89 ◽  
Author(s):  
WANMING CHEN ◽  
HUAWEI LIANG ◽  
TAO MEI ◽  
ZHUHONG YOU ◽  
SHIFU MIAO ◽  
...  
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Robot Navigation ◽  
Information Source ◽  
Low Complexity ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Distributed Information ◽  
Communication Method

Global Positioning System (GPS) is often used as a main information source for robot localization and navigation. However, it cannot be used in room or in field complex environment because of the bad signal there. To solve this problem, the authors designed and implemented a specific wireless sensor network (WSN) to provide information about the environment and indicate path for robot navigation. A two-stage auto-adaptive route selecting mechanism of the WSN was proposed to facilitate data relaying in localization and the robot's navigation. A low complexity localization algorithm was used to localize both the nodes and the robot. An indirect communication method was designed to make the communication between the WSN and the robot possible. In addition, a robot navigation method was proposed based on the wireless sensor network. In this method, the robot did not need to obtain the environment information; the wireless sensor nodes collected and fused the distributed information and then indicate a path for the robot. Experiments showed that the wireless sensor network can result in obstacle avoidance navigation, and can implement the online navigation.

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