Abstract
The objective of the autonomous navigation aims to achieve the self-motion control for a robot with the environmental feedbacks and becomes popular recently. Problems of complex modeling, large amo...
Highlights
Intelligent robot application areas expand into every walk of life such as the biped robots,[1,2,3] unmanned aerial vehicles,[4,5,6] mobile robots,[7] and so on
In order to illustrate the efficiency of the proposed FTGNM, it is compared with the visionbased navigation method,[8,23] where the objects are regarded as the same and the path is planned with all the sensed objects
An FTGMM is presented with dual 2-D grid maps describing a 3-D map to reduce the amount of calculation of mapping and path planning
Summary
Intelligent robot application areas expand into every walk of life such as the biped robots,[1,2,3] unmanned aerial vehicles,[4,5,6] mobile robots,[7] and so on. When judging the relationship of two sensed objects by fuzzy logic, assuming the distance between them is d, the ratio d=" is used as the input and the slave state possibility grade of the two objects is selected as the output, where " is the minimum detection difference between two obstacles and its value should be set according to the actual environment such as the measurement error of the sensors and the scale of each grid in the map. The information of the object which has been saved for the longest time in the dynamic storage area is deleted and ðx[0]; y0Þ is added instead In this way, the information of the static objects and the dynamic objects can be updated, and the coordinate information of the two sets can be shown on the map. In the proposed FTGNM, the objects are divided into the static objects and dynamic objects, and the corresponding
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
