Two-phase optimal path planning of autonomous ground vehicles using pseudo-spectral method

2014 ◽  
Vol 228 (4) ◽  
pp. 426-437 ◽  
Author(s):  
Behrooz Mashadi ◽  
Majid Majidi
Keyword(s):  
Path Planning ◽  
Spectral Method ◽  
Optimal Path ◽  
Ground Vehicles ◽  
Two Phase ◽  
Autonomous Ground Vehicles ◽  
Optimal Path Planning ◽  
Pseudo Spectral Method ◽  
Pseudo Spectral

Reliability-Based Mission Planning of Off-Road Autonomous Ground Vehicles Using an Outcrossing Approach

2021 ◽  
Author(s):  
Chen Jiang ◽  
Yixuan Liu ◽  
Zhen Hu ◽  
Zissimos P. Mourelatos ◽  
David Gorsich ◽  
...  
Keyword(s):  
Path Planning ◽  
Optimal Path ◽  
Gaussian Random Field ◽  
Mobility Model ◽  
Outcrossing Rate ◽  
Mission Planning ◽  
Ground Vehicles ◽  
Practical Applications ◽  
Autonomous Ground Vehicles ◽  
Uncertainty Sources

Abstract Reliability-based mission planning aims to identify an optimal path for off-road autonomous ground vehicles (AGVs) under uncertain terrain environment, while satisfying specific mission mobility reliability (MMR) constraints. The evaluation of MMR during path planning poses computational challenges for practical applications. This paper presents an efficient reliability-based mission planning using an outcrossing approach that has the same computational complexity as deterministic mission planning. A Gaussian random field is employed to represent the spatially dependent uncertainty sources in the terrain environment. The latter are then used in conjunction with a vehicle mobility model to generate a stochastic mobility map. Based on the stochastic mobility map, outcrossing rate maps are generated using the outcrossing concept which is widely used in time-dependent reliability. Integration of the outcrossing rate map with a rapidly-exploring random tree (RRT*) algorithm, allows for efficient path planning of AGVs subject to MMR constraints. A reliable RRT* algorithm using the outcrossing approach (RRT*-OC) is developed to implement the proposed efficient reliability-based mission planning. Results of a case study verify the accuracy and efficiency of the proposed algorithm.

scholarly journals An Intelligent Gain based Ant Colony Optimisation Method for Path Planning of Unmanned Ground Vehicles

2019 ◽  
Vol 69 (2) ◽  
pp. 167-172 ◽  
Author(s):  
Sangeetha Viswanathan ◽  
K. S. Ravichandran ◽  
Anand M. Tapas ◽  
Sellammal Shekhar
Keyword(s):  
Path Planning ◽  
Optimal Path ◽  
Computation Time ◽  
Ant Colony ◽  
Ant Colony Optimisation ◽  
Ground Vehicles ◽  
Optimal Path Planning ◽  
Military Applications ◽  
The Military ◽  
Reduction Cost

 In many of the military applications, path planning is one of the crucial decision-making strategies in an unmanned autonomous system. Many intelligent approaches to pathfinding and generation have been derived in the past decade. Energy reduction (cost and time) during pathfinding is a herculean task. Optimal path planning not only means the shortest path but also finding one in the minimised cost and time. In this paper, an intelligent gain based ant colony optimisation and gain based green-ant (GG-Ant) have been proposed with an efficient path and least computation time than the recent state-of-the-art intelligent techniques. Simulation has been done under different conditions and results outperform the existing ant colony optimisation (ACO) and green-ant techniques with respect to the computation time and path length.

Efficient Reliability-Based Mission Planning of Off-Road Autonomous Ground Vehicles Using an Outcrossing Approach

2021 ◽  
pp. 1-45
Author(s):  
Chen Jiang ◽  
Yixuan Liu ◽  
Zissimos P. Mourelatos ◽  
David Gorsich ◽  
Yan Fu ◽  
...  
Keyword(s):  
Path Planning ◽  
Optimal Path ◽  
Gaussian Random Field ◽  
Mobility Model ◽  
Outcrossing Rate ◽  
Mission Planning ◽  
Ground Vehicles ◽  
Practical Applications ◽  
Autonomous Ground Vehicles ◽  
Uncertainty Sources

Abstract Reliability-based mission planning aims to identify an optimal path for off-road autonomous ground vehicles (AGVs) under uncertain terrain environment, while satisfying specific mission mobility reliability (MMR) constraints. The evaluation of MMR during path planning poses computational challenges for practical applications. This paper presents an efficient reliability-based mission planning using an outcrossing approach that has the same computational complexity as deterministic mission planning. A Gaussian random field is employed to represent the spatially dependent uncertainty sources in the terrain environment. The latter are then used in conjunction with a vehicle mobility model to generate a stochastic mobility map. Based on the stochastic mobility map, outcrossing rate maps are generated using the outcrossing concept which is widely used in time-dependent reliability. Integration of the outcrossing rate map with a rapidly-exploring random tree (RRT*) algorithm, allows for efficient path planning of AGVs subject to MMR constraints. A reliable RRT* algorithm using the outcrossing approach (RRT*-OC) is developed to implement the proposed efficient reliability-based mission planning. Results of a case study with two scenarios verify the accuracy and efficiency of the proposed algorithm.

scholarly journals Modified Virtual Semi-Circle Approach for a Reactive Collision Avoidance of a Mobile Robot in an Outdoor Environment

2014 ◽  
Vol 679 ◽  
pp. 171-175 ◽  
Author(s):  
R.N. Farah ◽  
N. Irwan ◽  
Raja Lailatul Zuraida ◽  
Amira Shahirah ◽  
Mohd Hanafi Omar
Keyword(s):  
Path Planning ◽  
Optimal Path ◽  
Cost Effective ◽  
Outdoor Environment ◽  
Unmanned Ground Vehicle ◽  
Influence Zone ◽  
Two Phase ◽  
Ground Vehicle ◽  
Optimal Path Planning ◽  
Reactive Collision

There are numerous numbers of methods that have been introduced to the Unmanned Ground Vehicle (UGV) to find its optimal path. The purpose of this paper is to navigate a cost effective UGV known as MG-TruckS with optimal path planning in an outdoor environment. A Modified Virtual Semi Circle approach is proposed based on situated-activity paradigm. This approach is divided into two phase to compute a free collision path planning; detection and avoidance phase. Implementation of five ultrasonic range finder sensors with a very small blind zone created on purpose and the formation of three layers of influence zone shows the optimized path planning without making any unnecessary obstacle avoidance being computed.

scholarly journals An Overview of Nature-Inspired, Conventional, and Hybrid Methods of Autonomous Vehicle Path Planning

2018 ◽  
Vol 2018 ◽  
pp. 1-27 ◽  
Author(s):  
Ben Beklisi Kwame Ayawli ◽  
Ryad Chellali ◽  
Albert Yaw Appiah ◽  
Frimpong Kyeremeh
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Optimal Path ◽  
Mobile Robot Navigation ◽  
Planning Problem ◽  
Ground Vehicles ◽  
Robot Path Planning ◽  
Autonomous Ground Vehicles ◽  
Planning Methods ◽  
Robot Path

Safe and smooth mobile robot navigation through cluttered environment from the initial position to goal with optimal path is required to achieve intelligent autonomous ground vehicles. There are countless research contributions from researchers aiming at finding solution to autonomous mobile robot path planning problems. This paper presents an overview of nature-inspired, conventional, and hybrid path planning strategies employed by researchers over the years for mobile robot path planning problem. The main strengths and challenges of path planning methods employed by researchers were identified and discussed. Future directions for path planning research is given. The results of this paper can significantly enhance how effective path planning methods could be employed and implemented to achieve real-time intelligent autonomous ground vehicles.

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