scholarly journals Obstacle Detection for Unmanned Ground Vehicle on Uneven Terrain

2016 ◽  
Vol 65 (2) ◽  
pp. 342-348 ◽  
Author(s):  
Tok Son Choe ◽  
Sang Hyun Joo ◽  
Yong Woon Park ◽  
Jin Bae Park
Keyword(s):  
Obstacle Detection ◽  
Unmanned Ground Vehicle ◽  
Ground Vehicle ◽  
Uneven Terrain

Mobile Robot Decision-Making Based on Offline Simulation for Navigation over Uneven Terrain

2018 ◽  
Vol 30 (4) ◽  
pp. 671-682
Author(s):  
Yuichi Kobayashi ◽  
Masato Kondo ◽  
Yuji Hiramatsu ◽  
Hokuto Fujii ◽  
Tsuyoshi Kamiya ◽  
...  
Keyword(s):  
Mobile Robot ◽  
Path Selection ◽  
Outdoor Environment ◽  
Selection Strategy ◽  
Unmanned Ground Vehicle ◽  
Ground Vehicle ◽  
Uneven Terrain ◽  
Simulated Environment ◽  
Terrain Features ◽  
Selection Of

This paper presents an action decision framework for an autonomous mobile robot or an unmanned ground vehicle (UGV) to navigate an unknown environment. It is difficult for a UGV without global map information to decide which path to travel when it comes to a fork. However, locally observed terrain features can enable the UGV if it can utilize its past experience. The proposed path selection method utilizes correlations between features of the local terrain obtained by its laser range finder and the values of paths obtained through offline simulation using global path planning. During navigation, the UGV estimates the values of each path at a fork based on the correlation between the terrain feature and the value. It was confirmed that the proposed method allows the selection of paths that are more effective compared with a simple path selection strategy with which the UGV selects the closer path to the goal. The proposed method was evaluated in both a simulated environment and a real outdoor environment.

scholarly journals Obstacle Detection in Hybrid Cross-Country Environment Based on Markov Random Field for Unmanned Ground Vehicle

2015 ◽  
Vol 2015 ◽  
pp. 1-8
Author(s):  
Feng Ding ◽  
Yibing Zhao ◽  
Lie Guo ◽  
Mingheng Zhang ◽  
Linhui Li
Keyword(s):  
Random Field ◽  
Markov Random Field ◽  
Line Segment ◽  
Obstacle Detection ◽  
Corner Detection ◽  
Unmanned Ground Vehicle ◽  
Ground Vehicle ◽  
Markov Random ◽  
Cross Country ◽  
Hybrid Cross

In order to detect the obstacle from the large amount of 3D LIDAR data in hybrid cross-country environment for unmanned ground vehicle, a new graph approach based on Markov random field was presented. Firstly, the preprocessing method based on the maximum blurred line is applied to segment the projection of every laser scan line inx-yplane. Then, based onK-means clustering algorithm, the same properties of the line are combined. Secondly, line segment nodes are precisely positioned by using corner detection method, and the next step is to take advantage of line segment nodes to build an undirected graph for Markov random field. Lastly, the energy function is calculated by means of analyzing line segment features and solved by graph cut. Two types of line mark are finally classified into two categories: ground and obstacle. Experiments prove the feasibility of the approach and show that it has better performance and runs in real time.

scholarly journals Negotiating Uneven Terrain by a Simple Teleoperated Tracked Vehicle with Internally Movable Center of Gravity

2022 ◽  
Vol 12 (1) ◽  
pp. 525
Author(s):  
Yasuhiro Fukuoka ◽  
Kazuyuki Oshino ◽  
Ahmad Najmuddin Ibrahim
Keyword(s):  
Mechanical Design ◽  
Center Of Gravity ◽  
The Body ◽  
Unmanned Ground Vehicle ◽  
Tracked Vehicle ◽  
Ground Vehicle ◽  
High Position ◽  
Uneven Terrain ◽  
Dc Motors ◽  
Mass Position

We propose a mechanical design for a simple teleoperated unmanned ground vehicle (UGV) to negotiate uneven terrain. UGVs are typically classified into legged, legged-wheeled, wheeled, and tanked forms. Legged vehicles can significantly shift their center of gravity (COG) by positioning their multi-articulated legs at appropriate trajectories, stepping over a high obstacle. To realize a COG movable mechanism with a small number of joints, a number of UGVs have been developed that can shift their COG by moving a mass at a high position above the body. However, these tend to pose a risk of overturning, and the mass must be moved quite far to climb a high step. To address these issues, we design a novel COG shift mechanism, in which the COG can be shifted forward and backward inside the body by moving most of its internal devices. Since this movable mass includes DC motors for driving both tracks, we can extend the range of the COG movement. We demonstrate that a conventional tracked vehicle prototype can traverse a step and a gap between two steps, as well as climb stairs and a steep slope, with a human operating the vehicle movement and the movable mass position.

Obstacle detection for unmanned ground vehicle on uneven and dusty environment

2015 ◽  
Author(s):  
Tok Son Choe ◽  
Jin Bae Park ◽  
Sang Hyun Joo ◽  
Yong Woon Park
Keyword(s):  
Obstacle Detection ◽  
Unmanned Ground Vehicle ◽  
Ground Vehicle

PTEM Based Moving Obstacle Detection and Avoidance for an Unmanned Ground Vehicle

2017 ◽  
Author(s):  
Gangadhar Rajashekaraiah ◽  
Hakki Erhan Sevil ◽  
Atilla Dogan
Keyword(s):  
Obstacle Avoidance ◽  
Obstacle Detection ◽  
Mathematical Representation ◽  
Unmanned Ground Vehicle ◽  
Prior Work ◽  
Sensors And Actuators ◽  
Ground Vehicle ◽  
Simulink Simulation ◽  
Stationary Obstacles ◽  
Moving Obstacle

This study presents the development and implementation of an autonomous obstacle avoidance algorithm for an UGV (Unmanned Ground Vehicle). This research improves the prior work by enhancing the obstacle avoidance capability to handle moving obstacles as well as stationary obstacles. A mathematical representation of the area of operation with obstacles is formulated by PTEM (Probabilistic Threat Exposure Map). The PTEM quantifies the risk in being at a position in an area with different types of obstacles. A LRF (Laser Range Finder) sensor is mounted on the UGV for obstacle data in the area that is used to construct the PTEM. A guidance algorithm processes the PTEM and generates the speed and heading commands to steer the UGV to assigned waypoints while avoiding obstacles. The main contribution of this research is to improve the PTEM framework by updating it continuously as new LRF readings are obtained, on the contrary to the prior work with fixed PTEM. The improved PTEM construction algorithm is implemented in a MATLAB/Simulink simulation environment that includes models of the UGV, LRF, all the sensors and actuators needed for the control of the UGV. The performance of the algorithm is also demonstrated in real time experiments with an actual UGV system.

scholarly journals Design of a Mechanism with Embedded Suspension to Reconfigure the Agri_q Locomotion Layout

Robotics ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 15
Author(s):  
Carmen Visconte ◽  
Paride Cavallone ◽  
Luca Carbonari ◽  
Andrea Botta ◽  
Giuseppe Quaglia
Keyword(s):  
Precision Agriculture ◽  
Ground Contact ◽  
Unmanned Ground Vehicle ◽  
Kinematic Synthesis ◽  
Ground Vehicle ◽  
Uneven Terrain ◽  
Contact Points ◽  
Curved Trajectories ◽  
Wide Contact ◽  
Driving Torque

The Agri_q is an electric unmanned ground vehicle specifically designed for precision agriculture applications. Since it is expected to traverse on unstructured terrain, especially uneven terrain, or to climb obstacles or slopes, an eight-wheeled locomotion layout, with each pair of wheels supported by a bogie, has been chosen. The wide contact surface between the vehicle and the ground ensures a convenient weight distribution; furthermore, the bogie acts like a filter with respect to ground irregularities, reducing the transmissibility of the oscillations. Nevertheless, this locomotion layout entails a substantial lateral slithering along curved trajectories, which results in an increase of the needed driving torque. Therefore, reducing the number of ground contact points to compare the torque adsorption in different configurations, namely four, six, or eight wheels, could be of interest. This paper presents a reconfiguration mechanism able to modify the Agri_q locomotion layout by lifting one of the two wheels carried by the bogie and to activate, at the same time, a suspension device. The kinematic synthesis of the mechanism and the dynamic characteristics of the Agri_q suspended front module are presented.

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