Robot Mission Planning using Co-evolutionary Optimization

Robotica ◽  
2019 ◽  
Vol 38 (3) ◽  
pp. 512-530
Author(s):  
Kala Rahul
Keyword(s):  
Iterative Solution ◽  
Evolutionary Optimization ◽  
Model Verification ◽  
Mission Planning ◽  
Planning Problem ◽  
Design Heuristics ◽  
Verification Algorithms ◽  
Mission Specification ◽  
Exponential Complexity ◽  
Verification Techniques

SummaryMission planning is a complex motion planning problem specified by using Temporal Logic constituting of Boolean and temporal operators, typically solved by model verification algorithms with an exponential complexity. The paper proposes co-evolutionary optimization thus building an iterative solution to the problem. The language for mission specification is generic enough to represent everyday missions, while specific enough to design heuristics. The mission is broken into components which cooperate with each other. The experiments confirm that the robot is able to outperform the search, evolutionary and model verification techniques. The results are demonstrated by using a Pioneer LX robot.

scholarly journals Modeling and Simulation of Mission Planning Problem for Remote Sensing Satellite Imaging

2018 ◽  
Vol 179 ◽  
pp. 03024 ◽  
Author(s):  
Yao Pan ◽  
Zhong Ming Chi ◽  
Qi Long Rao ◽  
Kai Peng Sun ◽  
Yi Nan Liu
Keyword(s):  
Remote Sensing ◽  
Time Window ◽  
Constraint Satisfaction Problem ◽  
Optimal Path ◽  
Time Constraint ◽  
Mission Planning ◽  
Planning Problem ◽  
Satellite Imaging ◽  
Problem Model ◽  
Remote Sensing Satellite

Mission planning problem for remote sensing satellite imaging is studied. Firstly, the time constraint satisfaction problem model is presented after analyzing the characteristic of time constraint. Then, An optimal path searching algorithm based on the discrete time window is proposed according to the non-uniqueness for satellite to mission in the visible time window. Simulation results verify the efficiency of the model and algorithm.

scholarly journals A Hierarchical Cooperative Mission Planning Mechanism for Multiple Unmanned Aerial Vehicles

Electronics ◽  
2019 ◽  
Vol 8 (4) ◽  
pp. 443 ◽  
Author(s):  
Zhe Zhao ◽  
Jian Yang ◽  
Yifeng Niu ◽  
Yu Zhang ◽  
Lincheng Shen
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Search Algorithm ◽  
Pseudospectral Method ◽  
Task Assignment ◽  
Mission Planning ◽  
Planning Problem ◽  
B Spline ◽  
Aerial Vehicles ◽  
Third Stage ◽  
Multiple Unmanned Aerial Vehicles

In this paper, the cooperative multi-task online mission planning for multiple Unmanned Aerial Vehicles (UAVs) is studied. Firstly, the dynamics of unmanned aerial vehicles and the mission planning problem are studied. Secondly, a hierarchical mechanism is proposed to deal with the complex multi-UAV multi-task mission planning problem. In the first stage, the flight paths of UAVs are generated by the Dubins curve and B-spline mixed method, which are defined as “CBC)” curves, where “C” stands for circular arc and “B” stands for B-spline segment. In the second stage, the task assignment problem is solved as multi-base multi-traveling salesman problem, in which the “CBC” flight paths are used to estimate the trajectory costs. In the third stage, the flight trajectories of UAVs are generated by using Gaussian pseudospectral method (GPM). Thirdly, to improve the computational efficiency, the continuous and differential initial trajectories are generated based on the “CBC” flight paths. Finally, numerical simulations are presented to demonstrate the proposed approach, the designed initial solution search algorithm is compared with existing methods. These results indicate that the proposed hierarchical mission planning method can produce satisfactory mission planning results efficiently.

Uncertain UAV ISR mission planning problem with multiple correlated objectives

2017 ◽  
Vol 32 (1) ◽  
pp. 321-335 ◽  
Author(s):  
Zutong Wang ◽  
Mingfa Zheng ◽  
Jiansheng Guo ◽  
Hanqiao Huang
Keyword(s):  
Mission Planning ◽  
Planning Problem

Research on China Imaging Altimeter Planning Problem for Area Target Observation

2014 ◽  
Vol 667 ◽  
pp. 230-236
Author(s):  
Ya Mei Liu ◽  
Cong Min Lv ◽  
Hong Fei Wang
Keyword(s):  
Mathematical Model ◽  
Greedy Algorithm ◽  
Calculation Method ◽  
Constraint Propagation ◽  
Mission Planning ◽  
Planning Problem ◽  
Target Coverage ◽  
Propagation Algorithm ◽  
Complexity Constraints ◽  
Observation Period

The China Imaging Altimeter (CIALT) mission planning problem has complexity constraints. Overlap observation play a role in area target observation. Based on the analysis, the space gird was constructed. A calculation method for coverage percentage based on grid space statistic is proposed. A mathematical model of mission planning is established. A solving method combines constraint propagation algorithm and greedy algorithm is proposed. An area target mission with one month’s observation period was planned. The results showed that the method realized the goal that maximizing area target coverage in the shortest possible time and form the unique planning results at same observation requirements. It is applicable to CIALT area target observation planning.

Multiobjective Mission Planning for UAV under Uncertain Environment

2014 ◽  
Vol 556-562 ◽  
pp. 4435-4438
Author(s):  
Jing Yao Zhu ◽  
Qi Fang He ◽  
Tie Zhu Wang ◽  
Zu Tong Wang
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Uncertainty Theory ◽  
Multiobjective Programming ◽  
Flight Time ◽  
Programming Method ◽  
Mission Planning ◽  
Planning Problem ◽  
Uncertain Environment ◽  
Aerial Vehicles ◽  
Combat Environment

The combat environment of Unmanned Aerial Vehicles (UAVs) is filled with uncertain factors, which is complex and dynamic. This paper is devoted to the UAV mission planning problem under uncertain environment with three optimization objectives, such as flight time, fuel usage and threat imposed by enemy. Based on the uncertainty theory and multiobjective programming method, the UAV uncertain multiobjective mission plaaning model is built and solved.

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