UAV Path Planning in the Framework of MILP-Tropical Optimization

2017 ◽  
Author(s):  
Mohammadreza Radmanesh ◽  
Manish Kumar
Keyword(s):  
Path Planning ◽  
Numerical Study ◽  
Mixed Integer ◽  
Planning Problem ◽  
Fast Method ◽  
Tropical Mathematics ◽  
Tropical Optimization ◽  
Multiple Vehicles ◽  
And Performance ◽  
New Framework

This paper proposes a fast method for obtaining mathematically optimal trajectories for UAVs while avoiding collisions. A comparison of the proposed method with previously used Mixed Integer Linear Programming (MILP) to find the optimal collision-free path UAVs, aircraft, and spacecraft show the effectiveness and performance of this method. Here, the UAV path planning problem is formulated in the new framework named MILP-Tropical optimization that exploits tropical mathematics for obtaining solution and then casted in a novel branch-and-bound method. Various constraints including UAV dynamics are incorporated in the proposed Tropical framework and a solution methodology is presented. An extensive numerical study shows that the proposed method provides faster solution. The proposed technique can be extended to distributed control for multiple vehicles and multiple way-points.

Optimal Operation of a Gogeneration Plant in Consideration of Equipment Startup/Shutdown Cost

1999 ◽  
Vol 121 (4) ◽  
pp. 254-261 ◽  
Author(s):  
R. Yokoyama ◽  
K. Ito
Keyword(s):  
Energy Supply ◽  
Large Scale ◽  
Numerical Study ◽  
District Heating ◽  
Computation Time ◽  
Optimal Operation ◽  
Operational Planning ◽  
Mixed Integer ◽  
Planning Problem ◽  
Operational Strategy

A rational method of determining the operational strategy of energy supply plants in consideration of equipment startup/shutdown cost is proposed. The operational planning problem is formulated as a large-scale mixed-integer linear programming one, in which on/off status and energy flow rates of equipment are determined so as to minimize the sum of energy supply and startup/shutdown costs over the period considered. By utilizing a special structure of the problem, an algorithm of solving the problem efficiently is proposed. Through a numerical study on the daily operational planning of a gas turbine cogeneration plant for district heating and cooling, the effectiveness of the proposed algorithm, is ascertained in terms of computation time, and the influence of equipment startup/shutdown cost on the operational strategy and cost is clarified.

scholarly journals Single Real Goal, Magnitude-Based Deceptive Path-Planning

Entropy ◽  
2020 ◽  
Vol 22 (1) ◽  
pp. 88 ◽  
Author(s):  
Kai Xu ◽  
Yunxiu Zeng ◽  
Long Qin ◽  
Quanjun Yin
Keyword(s):  
Integer Programming ◽  
Path Planning ◽  
Real World ◽  
Mixed Integer ◽  
Public Security ◽  
Planning Problem ◽  
Recent Developments ◽  
Goal Recognition ◽  
Path Planning Problem ◽  
Real Goal

Deceptive path-planning is the task of finding a path so as to minimize the probability of an observer (or a defender) identifying the observed agent’s final goal before the goal has been reached. It is one of the important approaches to solving real-world challenges, such as public security, strategic transportation, and logistics. Existing methods either cannot make full use of the entire environments’ information, or lack enough flexibility for balancing the path’s deceptivity and available moving resource. In this work, building on recent developments in probabilistic goal recognition, we formalized a single real goal magnitude-based deceptive path-planning problem followed by a mixed-integer programming based deceptive path maximization and generation method. The model helps to establish a computable foundation for any further imposition of different deception concepts or strategies, and broadens its applicability in many scenarios. Experimental results showed the effectiveness of our methods in deceptive path-planning compared to the existing one.

scholarly journals An optimal path planning problem for heterogeneous multi-vehicle systems

2016 ◽  
Vol 26 (2) ◽  
pp. 297-308 ◽  
Author(s):  
Martin Klaučo ◽  
Slavomír Blažek ◽  
Michal Kvasnica
Keyword(s):  
Path Planning ◽  
A Priori ◽  
Optimal Path ◽  
Mixed Integer ◽  
Planning Problem ◽  
Optimal Path Planning ◽  
Second Order Cone ◽  
Vehicle Systems ◽  
Close Distance ◽  
Path Planning Problem

Abstract A path planning problem for a heterogeneous vehicle is considered. Such a vehicle consists of two parts which have the ability to move individually, but one of them has a shorter range and is therefore required to keep in a close distance to the main vehicle. The objective is to devise an optimal path of minimal length under the condition that at least one part of the heterogeneous system visits all desired waypoints exactly once. Two versions of the problem are considered. One assumes that the order in which the waypoints are visited is known a priori. In such a case we show that the optimal path can be found by solving a mixed-integer second-order cone problem. The second version assumes that the order in which the waypoints are visited is not known a priori, but can be optimized so as to shorten the length of the path. Two approaches to solve this problem are presented and evaluated with respect to computational complexity.

scholarly journals Optimizing Coverage Performance of Multiple Random Path-planning Robots

2012 ◽  
Vol 3 (1) ◽  
Author(s):  
Md Ahsan Habib ◽  
M.S. Alam ◽  
N.H. Siddique
Keyword(s):  
Path Planning ◽  
Planning Problem ◽  
Coverage Path Planning ◽  
Simulated Environment ◽  
Planning Algorithm ◽  
Multi Agent ◽  
And Performance ◽  
Unknown Area ◽  
Path Planning Algorithm ◽  
Multi Robot

AbstractThis paper presents a new approach to the multi-agent coverage path-planning problem. An efficient multi-robot coverage algorithm yields a coverage path for each robot, such that the union of all paths generates an almost full coverage of the terrain and the total coverage time is minimized. The proposed algorithm enables multiple robots with limited sensor capabilities to perform efficient coverage on a shared territory. Each robot is assigned to an exclusive route which enables it to carry out its tasks simultaneously, e.g., cleaning assigned floor area with minimal path overlapping. It is very difficult to cover all free space without visiting some locations more than once, but the occurrence of such events can be minimized with efficient algorithms. The proposed multi-robot coverage strategy directs a number of simple robots to cover an unknown area in a systematic manner. This is based on footprint data left by the randomized path-planning robots previously operated on that area. The developed path-planning algorithm has been applied to a simulated environment and robots to verify its effectiveness and performance in such an application.

scholarly journals Optimal Operation of a Gas Turbine Cogeneration Plant in Consideration of Equipment Startup/Shutdown Cost

1997 ◽  
Author(s):  
Ryohei Yokoyama ◽  
Koichi Ito
Keyword(s):  
Gas Turbine ◽  
Energy Supply ◽  
Large Scale ◽  
Numerical Study ◽  
Optimal Operation ◽  
Operational Planning ◽  
Mixed Integer ◽  
Planning Problem ◽  
Cogeneration Plant ◽  
Operational Strategy

A rational method of determining the operational strategy of energy supply plants in consideration of equipment startup/shutdown cost is proposed. The operational planning problem is formulated as a large-scale mixed-integer linear programming one, in which on/off status and energy flow rates of equipment are determined so as to minimize the sum of energy supply and startup/shutdown costs over the period considered. By utilizing a special structure of the problem, an algorithm of solving the problem efficiently is proposed. Through a numerical study on the daily operational planning of a gas turbine cogeneration plant for district heating and cooling, the effectiveness of the proposed algorithm is ascertained in terms of computation time, and the influence of equipment startup/shutdown cost on the operational strategy and cost is clarified.

Operational Strategy of a Cogeneration System Under a Complex Utility Rate Structure

1996 ◽  
Vol 118 (4) ◽  
pp. 256-262 ◽  
Author(s):  
R. Yokoyama ◽  
K. Ito
Keyword(s):  
Energy Demand ◽  
Large Scale ◽  
Numerical Study ◽  
Mixed Integer ◽  
Planning Problem ◽  
Total Utility ◽  
Operational Strategy ◽  
Rate Structure ◽  
Cogeneration System ◽  
Utility Rate

An operational planning problem for a cogeneration system is discussed under a complex utility rate structure which imposes demand charges due to total utility consumption over a specified period as well as demand and energy charges due to hourly utility consumption. Operational strategy of constituent equipment and contract demands for total utility consumption are assessed so as to minimize the operational cost over the period subject to energy demand requirement. This problem is formulated as a large-scale mixed-integer linear programming (MILP) one, and it is solved efficiently by a revised decomposition method for MILP problems with block angular structure. Through a numerical study on a gas engine-driven cogeneration system installed in a hotel or an office building, the effect of rate structure on operational strategy is clarified.

Research on pull-type multi-AGV system dynamic path optimization based on time window

2021 ◽  
pp. 095440702098271
Author(s):  
Hongying Shan ◽  
Chuang Wang ◽  
Cungang Zou ◽  
Mengyao Qin
Keyword(s):  
Path Planning ◽  
Time Window ◽  
Planning Problem ◽  
Dijkstra Algorithm ◽  
Before And After ◽  
Common Planning ◽  
Planning Algorithm ◽  
Dynamic Path ◽  
Set Up ◽  
Path Planning Algorithm

This paper is a study of the dynamic path planning problem of the pull-type multiple Automated Guided Vehicle (multi-AGV) complex system. First, based on research status at home and abroad, the conflict types, common planning algorithms, and task scheduling methods of different AGV complex systems are compared and analyzed. After comparing the different algorithms, the Dijkstra algorithm was selected as the path planning algorithm. Secondly, a mathematical model is set up for the shortest path of the total driving path, and a general algorithm for multi-AGV collision-free path planning based on a time window is proposed. After a thorough study of the shortcomings of traditional single-car planning and conflict resolution algorithms, a time window improvement algorithm for the planning path and the solution of the path conflict covariance is established. Experiments on VC++ software showed that the improved algorithm reduces the time of path planning and improves the punctual delivery rate of tasks. Finally, the algorithm is applied to material distribution in the OSIS workshop of a C enterprise company. It can be determined that the method is feasible in the actual production and has a certain application value by the improvement of the data before and after the comparison.

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