Name
Title | ||
|---|---|---|
Sensor-based autonomous robot navigation under unknown environments with grid map representation |
Abstract | ||
|---|---|---|
Real-time navigation and mapping of an autonomous robot is one of the major challenges in intelligent robot systems. In this paper, a novel sensor-based biologically inspired neural network algorithm to real-time collision-free navigation and mapping of an autonomous mobile robot in a completely unknown environment is proposed. A local map composed of square grids is built up through the proposed neural dynamics for robot navigation with restricted incoming sensory information. With equipped sensors, the robot can only sense a limited reading range of surroundings with grid map representation. According to the measured sensory information, an accurate map with grid representation of the robot with local environment is dynamically built for the robot navigation. The real-time robot motion is planned through the varying neural activity landscape, which represents the dynamic environment. The proposed model for autonomous robot navigation and mapping is capable of planning a real-time reasonable trajectory of an autonomous robot. Simulation and comparison studies are presented to demonstrate the effectiveness and efficiency of the proposed methodology that concurrently performs collision-free navigation and mapping of an intelligent robot. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/SIS.2014.7011782 | SIS |
Keywords | Field | DocType |
local map,intelligent robot systems,neurocontrollers,real-time reasonable trajectory planning,real-time robot motion planning,mobile robots,unknown environments,sensor-based autonomous mobile robot navigation,intelligent robots,real-time collision-free navigation,trajectory control,varying neural activity landscape,sensors,grid map representation,collision avoidance,sensor-based biologically inspired neural network algorithm,real-time collision-free mapping,navigation | Robot learning,Grid reference,Robot control,Computer vision,Robot calibration,Artificial intelligence,Mobile robot navigation,Robot,Autonomous robot,Geography,Mobile robot | Conference |
Citations | PageRank | References |
0 | 0.34 | 12 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chaomin Luo | 1 | 186 | 19.40 |
| Jiyong Gao | 2 | 0 | 0.34 |
| Xinde Li | 3 | 50 | 11.00 |
| MO Hong-wei | 4 | 54 | 11.83 |
| Qimi Jiang | 5 | 0 | 0.34 |