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 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.

Unmanned Ground Vehicle SysML Navigation Model Conducted by Energy Efficiency

2014 ◽  
Vol 905 ◽  
pp. 443-447
Author(s):  
Eero Väljaots ◽  
Raivo Sell
Keyword(s):  
Mobile Robot ◽  
Design Methodology ◽  
Design Stage ◽  
Unmanned Ground Vehicle ◽  
Ground Vehicle ◽  
Early Design ◽  
Early Design Stage ◽  
Detail Design ◽  
Snow Plowing ◽  
Robot Platform

In this paper a SysML navigation models and early design methodology is briefly introduced. The methodology is offering tool and pre-defined models for mobile robot design in early design stage. The main target is reaching the optimal and efficient conceptual solution for detail design stage by using the pre-defined and validated SysML models according to the robot purpose and missions. As an example a snow plowing mission is demonstrated. Real mobile robot platform called UKU is developed and used for model validation purpose.

scholarly journals An Imaging Network Design for UGV-Based 3D Reconstruction of Buildings

2021 ◽  
Vol 13 (10) ◽  
pp. 1923
Author(s):  
Ali Hosseininaveh ◽  
Fabio Remondino
Keyword(s):  
3D Reconstruction ◽  
Network Design ◽  
Real World ◽  
Continuous Image ◽  
Unmanned Ground Vehicle ◽  
Ground Vehicle ◽  
Localization And Mapping ◽  
Image Capturing ◽  
Slam Algorithm ◽  
Selection Of

Imaging network design is a crucial step in most image-based 3D reconstruction applications based on Structure from Motion (SfM) and multi-view stereo (MVS) methods. This paper proposes a novel photogrammetric algorithm for imaging network design for building 3D reconstruction purposes. The proposed methodology consists of two main steps: (i) the generation of candidate viewpoints and (ii) the clustering and selection of vantage viewpoints. The first step includes the identification of initial candidate viewpoints, selecting the candidate viewpoints in the optimum range, and defining viewpoint direction stages. In the second step, four challenging approaches—named façade pointing, centre pointing, hybrid, and both centre & façade pointing—are proposed. The entire methodology is implemented and evaluated in both simulation and real-world experiments. In the simulation experiment, a building and its environment are computer-generated in the ROS (Robot Operating System) Gazebo environment and a map is created by using a simulated robot and Gmapping algorithm based on a Simultaneously Localization and Mapping (SLAM) algorithm using a simulated Unmanned Ground Vehicle (UGV). In the real-world experiment, the proposed methodology is evaluated for all four approaches for a real building with two common approaches, called continuous image capturing and continuous image capturing & clustering and selection approaches. The results of both evaluations reveal that the fusion of centre & façade pointing approach is more efficient than all other approaches in terms of both accuracy and completeness criteria.

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

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.

scholarly journals Scoring Cercospora Leaf Spot on Sugar Beet: Comparison of UGV and UAV Phenotyping Systems

2020 ◽  
Vol 2020 ◽  
pp. 1-18 ◽  
Author(s):  
S. Jay ◽  
A. Comar ◽  
R. Benicio ◽  
J. Beauvois ◽  
D. Dutartre ◽  
...  
Keyword(s):  
Sugar Beet ◽  
Leaf Spot ◽  
Spot Size ◽  
Unmanned Ground Vehicle ◽  
Cercospora Leaf Spot ◽  
Ground Vehicle ◽  
Aerial Vehicle ◽  
High Throughput Phenotyping ◽  
Selection Of ◽  
Genotype Sensitivity

Selection of sugar beet (Beta vulgaris L.) cultivars that are resistant to Cercospora Leaf Spot (CLS) disease is critical to increase yield. Such selection requires an automatic, fast, and objective method to assess CLS severity on thousands of cultivars in the field. For this purpose, we compare the use of submillimeter scale RGB imagery acquired from an Unmanned Ground Vehicle (UGV) under active illumination and centimeter scale multispectral imagery acquired from an Unmanned Aerial Vehicle (UAV) under passive illumination. Several variables are extracted from the images (spot density and spot size for UGV, green fraction for UGV and UAV) and related to visual scores assessed by an expert. Results show that spot density and green fraction are critical variables to assess low and high CLS severities, respectively, which emphasizes the importance of having submillimeter images to early detect CLS in field conditions. Genotype sensitivity to CLS can then be accurately retrieved based on time integrals of UGV- and UAV-derived scores. While UGV shows the best estimation performance, UAV can show accurate estimates of cultivar sensitivity if the data are properly acquired. Advantages and limitations of UGV, UAV, and visual scoring methods are finally discussed in the perspective of high-throughput phenotyping.

Sign in / Sign up

Export Citation Format

Share Document