scholarly journals Coverage path planning for a flock of aerial vehicles to support autonomous rovers through traversability analysis

ACTA IMEKO ◽  
2019 ◽  
Vol 8 (4) ◽  
pp. 9 ◽  
Author(s):  
Dario Calogero Guastella ◽  
Luciano Cantelli ◽  
Domenico Longo ◽  
Carmelo Donato Melita ◽  
Giovanni Muscato

In rough terrains, such as landslides or volcanic eruptions, it is extremely complex to plan safe trajectories for an Unmanned Ground Vehicle (UGV), since both robot stability and path execution feasibility must be guaranteed. In this paper, we present a complete solution for the autonomous navigation of ground vehicles in the mentioned scenarios. The proposed solution integrates three different aspects. The first is the coverage path planning for the definition of UAV trajectories for aerial imagery acquisition. The collected images are used for the photogrammetric reconstruction of the considered area. The second aspect is the adoption of a flock of UAVs to implement the coverage in a parallel way. In fact, when non-coverable zones are present, decomposition of the whole area to survey is performed. A solution to assign the different regions among the flying vehicles composing the team is presented. The last aspect is the path planning of the ground vehicle by means of a traversability analysis performed on the terrain 3D model. The computed paths are optimal in terms of the difficulty of moving across the rough terrain. The results of each step within the overall approach are shown.

2018 ◽  
Vol 06 (04) ◽  
pp. 251-266
Author(s):  
Phillip J. Durst ◽  
Christopher T. Goodin ◽  
Cindy L. Bethel ◽  
Derek T. Anderson ◽  
Daniel W. Carruth ◽  
...  

Path planning plays an integral role in mission planning for ground vehicle operations in urban areas. Determining the optimum path through an urban area is a well-understood problem for traditional ground vehicles; however, in the case of autonomous unmanned ground vehicles (UGVs), additional factors must be considered. For an autonomous UGV, perception algorithms rather than platform mobility will be the limiting factor in operational capabilities. For this study, perception was incorporated into the path planning process by associating sensor error costs with traveling through nodes within an urban road network. Three common perception sensors were used for this study: GPS, LIDAR, and IMU. Multiple set aggregation operators were used to blend the sensor error costs into a single cost, and the effects of choice of aggregation operator on the chosen path were observed. To provide a robust path planning ability, a fuzzy route planning algorithm was developed using membership functions and fuzzy rules to allow for qualitative route planning in the case of generalized UGV performance. The fuzzy membership functions were then applied to several paths through the urban area to determine what sensors were optimized in each path to provide a measure of the UGV’s performance capabilities. The research presented in this paper shows the impacts that sensing/perception has on ground vehicle route planning by demonstrating a fuzzy route planning algorithm constructed by using a robust rule set that quantifies these impacts.


2016 ◽  
Vol 78 (6-6) ◽  
Author(s):  
R. N. Farah ◽  
Amira Shahirah ◽  
N. Irwan ◽  
R. L. Zuraida

The challenging part of path planning for an Unmanned Ground Vehicle (UGV) is to conduct a reactive navigation. Reactive navigation is implemented to the sensor based UGV. The UGV defined the environment by collecting the information to construct it path planning. The UGV in this research is known as Mobile Guard UGV-Truck for Surveillance (MG-TruckS). Modified Virtual Semi Circle (MVSC) helps the MG-TruckS to reach it predetermined goal point successfully without any collision. MVSC is divided into two phases which are obstacles detection phase and obstacles avoidance phase to compute an optimal path planning. MVSC produces shorter path length, smoothness of velocity and reach it predetermined goal point successfully.


Author(s):  
Mostafa Salama ◽  
Vladimir V. Vantsevich

Studies of the tire-terrain interaction have mostly been completed on vehicles with steered wheels, but not much work has been done regarding skid-steered Unmanned Ground Vehicles (UGV). This paper introduces a mathematical model of normal and longitudinal dynamics of a UGV with four skid-steered pneumatic tire wheels. Unlike the common approach, in which two wheels at each side are treated as one wheel (i.e., having the same rotational speeds), all four wheels in this study are independently driven. Thus the interaction of each tire with deformable terrain is introduced as holonomic constraints. The stress-strain characteristics for tire-soil interaction are analyzed based on modern Terramechanics methods and then further used to determine the circumferential wheel forces of the four tires. Contributions of three components of each tire circumferential force to tire slippages are modeled and analyzed when the tire normal loads vary during vehicle straight-line motion. The considered tire-soil characteristics are mathematically reduced to a form that allows condensing the computational time for on-line computing tire-terrain characteristics. Additionally, rolling resistance of the tires is analyzed and incorporated in the UGV dynamic equations. Moreover, the paper describes the physics of slip power losses in the tire-soil interaction of the four tires and applies it to small skid-steered UGV. This study also formulates an optimization problem of the minimization of the power losses in the tire-soil interactions due to the tire slippage.


Author(s):  
Jurgen Zoto ◽  
Maria Angela Musci ◽  
Aleem Khaliq ◽  
Marcello Chiaberge ◽  
Irene Aicardi

Author(s):  
Madan M. Dabbeeru ◽  
Joshua D. Langsfeld ◽  
Petr Svec ◽  
Satyandra K. Gupta

This paper focuses on the development of a follow behavior for an unmanned ground vehicle (UGV) in collaborative scenarios. The scenario being studied involves a human traveling over a rugged terrain on foot. The UGV follows the human. We present an approach for automatically generating a reactive energy-efficient follow behavior that maps the vehicle’s states into motion goals. We start by partitioning the state space that encodes the relationship between the state of the vehicle and the human’s state, and the environment. For each cell in the partitioned state space, we either directly generate the motion goal for the vehicle to execute or a function that produces the motion goal. The motion goal defines not only the location towards which the vehicle should move but also specifies a zero activity zone around the human within which the vehicle is supposed to slow down and remain stationary to save its energy until it gets outside the margin caused by the movement of the human. Our approach utilizes off-line simulations to assess the performance of the generated behavior. Our simulation results show that the automatically generated follow behavior significantly outperforms a simple conservative tracking rule in terms of distance traveled and violation of proximity constraints. We anticipate that the approach presented in this paper will ultimately enable us to implement energy efficient follow behaviors on physical UGVs.


Author(s):  
S. Narayan ◽  
T. V. Prasannakumar ◽  
M. Prasanth ◽  
N. Praveen Velavan ◽  
N. Praveen Kumar ◽  
...  

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