Abstract
A new 3D localization and mapping technique with terrain inclination assistance is proposed in this paper to allow a robot to identify its location and build a global map in an outdoor environment. The Iterative Closest Points (ICP) algorithm and terrain inclination-based localization are combined together to achieve accurate and fast localization and mapping. Inclinations of the terrains the robot navigates are used to achieve local localization during the interval between two laser scans. Using the results of the above localization as the initial condition, the ICP algorithm is then applied to align the overlapped laser scan maps to update the overhanging obstacles for building a global map of the surrounding area. Comprehensive experiments were carried out for the validation of the proposed 3D localization and mapping technique. The experimental results show that the proposed technique could reduce time consumption and improve the accuracy of the performance.
Highlights
Laser range sensors have been widely used in outdoor environments to achieve localization and mapping because they can provide accurate and ample point clouds of the surrounding environment
The goal of this research is to provide a less computationally‐demanding and more accurate 3D localization and mapping approach with terrain inclination assistance for the mobile robot navigating on inclined terrains
The NAV440 from Crossbow Technology was used as the inertial measurement unit (IMU) that mounted on the robot in order to measure the roll, pitch, sfsyvoyyazrsswbwtteeaaammrrendgwwblseioaptstshehaepnndrzodoe‐svrvtlohiixdpbeewaadwisntsibhgutyhumrltearphesrtepsivpoeeeecnnltco.ctcotiotdtoieetrtshhsee oxrfrbootb,hb ooettyrbocc,oob ooozrrtbdd. .iivnnTyaahbtteee, An outdoor environment is selected around the library of the Shenzhen University Town with the 3D terrains www.intechopen.com
Summary
Laser range sensors have been widely used in outdoor environments to achieve localization and mapping because they can provide accurate and ample point clouds of the surrounding environment. The goal of this research is to provide a less computationally‐demanding and more accurate 3D localization and mapping approach with terrain inclination assistance for the mobile robot navigating on inclined terrains. Mobile robots have been increasingly widely applied in many different scenarios, such as space exploration [1] and search and rescue [2], where the robots are required to travel over uneven terrain while outdoors. Many aspects of research on mobile robots operating in uneven terrains have been studied, such as rough terrain modelling [3, 4], terrain characterization [5, 6] and motion planning and control [4].
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