Multi-Criteria Mission Planning for a Solar-Powered Multi-Robot System

2018 ◽  
Author(s):  
Di Wang ◽  
Mengqi Hu ◽  
Yang Gao
Keyword(s):  
Energy Consumption ◽  
Solar Energy ◽  
Time Window ◽  
Mission Planning ◽  
Mixed Integer ◽  
Robot System ◽  
Efficient Operation ◽  
Operational Life ◽  
Solar Powered ◽  
Multi Robot

Recent years have witnessed a tremendous growth of interest in multi-robot system which can execute more complex tasks compared to single robot. To improve the operational life of multi-robot system and address challenges in long-duration mission, the solar-powered multi-robot system has been demonstrated to be an effective solution. To ensure efficient operation of solar-powered multi-robot system, we propose a multi-criteria mixed integer programming model for multi-robot mission planning to minimize three objectives including traveling distance, traveling time, and net energy consumption. Our proposed model is an extension of multiple vehicle routing problem considering time window, flexible speed, and energy sharing where a set of flexible speeds are proposed to explore the influence of robot’s velocity on energy consumption and solar energy harvesting. Three sets of case studies are designed to investigate the tradeoffs among the three objectives. The results demonstrate that heterogeneous multi-robot system: 1) can more efficiently utilize solar energy and 2) need a multi-criteria model to balance the three objectives.

Cooperative Mission Planning with Multiple UAVs in Realistic Environments

2014 ◽  
Vol 02 (01) ◽  
pp. 73-86 ◽  
Author(s):  
L. Geng ◽  
Y. F. Zhang ◽  
Jingjing Wang ◽  
Jerry Y. H. Fuh ◽  
S. H. Teo
Keyword(s):  
Vehicle Routing Problem ◽  
Time Window ◽  
Task Assignment ◽  
Mission Planning ◽  
Planning System ◽  
Mixed Integer ◽  
A Algorithm ◽  
Routing Problem ◽  
Second Stage ◽  
Multiple Uavs

In this paper, a mission planning system is developed for managing multiple unmanned aerial vehicles (UAVs) of various capabilities to execute a series of missions over multiple targets. A target may need up to three tasks (i.e., classification, attack, and verification) to be carried out in sequence. The problem is addressed in two decision-making stages. First, the shortest feasible flying path for a UAV to fly between any pair of task locations is obtained using a customized A* algorithm. During the search, constraints such as collision avoidance from terrain, circumvention of flight prohibition zones, and the flying capabilities of UAVs are considered. In the second stage, with the obtained UAV flying paths between task locations, mission planning is modeled as a vehicle routing problem (VRP) with time window and precedence requirements. A genetic algorithm with a built-in mixed integer programming (MIP) solver is developed to solve the problem. The outputs of this proposed planning system include (1) task assignment among the UAVs, (2) mission execution schedule for each UAV, and (3) flying paths of the UAVs.

scholarly journals UAV Mission Planning with SAR Application

Sensors ◽  
2020 ◽  
Vol 20 (4) ◽  
pp. 1080 ◽  
Author(s):  
Wojciech Stecz ◽  
Krzysztof Gromada
Keyword(s):  
Time Window ◽  
Scheduling Algorithm ◽  
Time Windows ◽  
Route Planning ◽  
Mission Planning ◽  
Mixed Integer ◽  
Technical Parameters ◽  
Aerial Vehicle ◽  
Flight Route ◽  
Electronic Intelligence

The paper presents the concept of mission planning for a short-range tactical class Unmanned Aerial Vehicle (UAV) that recognizes targets using the sensors it has been equipped with. Tasks carried out by such systems are mainly associated with aerial reconnaissance employing Electro Optical (EO)/Near Infra-Red (NIR) heads, Synthetic Aperture Radar (SAR), and Electronic Intelligence (ELINT) systems. UAVs of this class are most often used in NATO armies to support artillery actions, etc. The key task, carried out during their activities, is to plan a reconnaissance mission in which the flight route will be determined that optimally uses the sensors’ capabilities. The paper describes the scenario of determining the mission plan and, in particular, the UAV flight routes to which the recognition targets are assigned. The problem was decomposed into several subproblems: assigning reconnaissance tasks to UAVs with choosing the reconnaissance sensors and designating an initial UAV flight plan. The last step is planning a detailed flight route taking into account the time constraints imposed on recognition and the characteristics of the reconnaissance sensors. The final step is to generate the real UAV flight trajectory based on its technical parameters. The algorithm for determining exact flight routes for the indicated reconnaissance purposes was also discussed, taking into account the presence of enemy troops and available air corridors. The task scheduling algorithm—Vehicle Route Planning with Time Window (VRPTW)—using time windows is formulated in the form of the Mixed Integer Linear Problem (MILP). The MILP formulation was used to solve the UAV flight route planning task. The algorithm can be used both when planning individual UAV missions and UAV groups cooperating together. The approach presented is a practical way of establishing mission plans implemented in real unmanned systems.

scholarly journals Reinforcement-Learning-Based Asynchronous Formation Control Scheme for Multiple Unmanned Surface Vehicles

2021 ◽  
Vol 11 (2) ◽  
pp. 546
Author(s):  
Jiajia Xie ◽  
Rui Zhou ◽  
Yuan Liu ◽  
Jun Luo ◽  
Shaorong Xie ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Formation Control ◽  
Rapid Development ◽  
Gradient Algorithm ◽  
Robot System ◽  
Physical Relationship ◽  
Unmanned Surface Vehicles ◽  
Main Challenge ◽  
Control Scheme ◽  
Multi Robot

The high performance and efficiency of multiple unmanned surface vehicles (multi-USV) promote the further civilian and military applications of coordinated USV. As the basis of multiple USVs’ cooperative work, considerable attention has been spent on developing the decentralized formation control of the USV swarm. Formation control of multiple USV belongs to the geometric problems of a multi-robot system. The main challenge is the way to generate and maintain the formation of a multi-robot system. The rapid development of reinforcement learning provides us with a new solution to deal with these problems. In this paper, we introduce a decentralized structure of the multi-USV system and employ reinforcement learning to deal with the formation control of a multi-USV system in a leader–follower topology. Therefore, we propose an asynchronous decentralized formation control scheme based on reinforcement learning for multiple USVs. First, a simplified USV model is established. Simultaneously, the formation shape model is built to provide formation parameters and to describe the physical relationship between USVs. Second, the advantage deep deterministic policy gradient algorithm (ADDPG) is proposed. Third, formation generation policies and formation maintenance policies based on the ADDPG are proposed to form and maintain the given geometry structure of the team of USVs during movement. Moreover, three new reward functions are designed and utilized to promote policy learning. Finally, various experiments are conducted to validate the performance of the proposed formation control scheme. Simulation results and contrast experiments demonstrate the efficiency and stability of the formation control scheme.

scholarly journals Research Progress on Synergistic Technologies of Agricultural Multi-Robots

2021 ◽  
Vol 11 (4) ◽  
pp. 1448
Author(s):  
Wenju Mao ◽  
Zhijie Liu ◽  
Heng Liu ◽  
Fuzeng Yang ◽  
Meirong Wang
Keyword(s):  
Path Planning ◽  
Formation Control ◽  
Research Progress ◽  
Hybrid Architecture ◽  
Labor Costs ◽  
Robot System ◽  
System Architectures ◽  
Research Results ◽  
Robot Systems ◽  
Multi Robot

Multi-robots have shown good application prospects in agricultural production. Studying the synergistic technologies of agricultural multi-robots can not only improve the efficiency of the overall robot system and meet the needs of precision farming but also solve the problems of decreasing effective labor supply and increasing labor costs in agriculture. Therefore, starting from the point of view of an agricultural multiple robot system architectures, this paper reviews the representative research results of five synergistic technologies of agricultural multi-robots in recent years, namely, environment perception, task allocation, path planning, formation control, and communication, and summarizes the technological progress and development characteristics of these five technologies. Finally, because of these development characteristics, it is shown that the trends and research focus for agricultural multi-robots are to optimize the existing technologies and apply them to a variety of agricultural multi-robots, such as building a hybrid architecture of multi-robot systems, SLAM (simultaneous localization and mapping), cooperation learning of robots, hybrid path planning and formation reconstruction. While synergistic technologies of agricultural multi-robots are extremely challenging in production, in combination with previous research results for real agricultural multi-robots and social development demand, we conclude that it is realistic to expect automated multi-robot systems in the future.

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 Optically tracked multi-robot system for keyhole neurosurgery

2011 ◽  
Author(s):  
Mirko Daniele Comparetti ◽  
Elena De Momi ◽  
Alberto Vaccarella ◽  
Matthias Riechmann ◽  
Giancarlo Ferrigno
Keyword(s):  
Robot System ◽  
Multi Robot
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