Collaborative Mission Planning &amp; Autonomous Control Technology (CoMPACT) System Employing Swarms of UAVs

Boskovic, J.D.; Knoebel, Nathan; Moshtagh, Nima; Amin, Jayesh; Larson, Gregory

doi:10.2514/6.2009-5653

Cited by 29 publications

(16 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In frame of military activities, some studies [5] have been done about UAVs swarms in contexts of collaborative mission planning for Intelligence, Surveillance and Reconnaissance (ISR) missions. Path planning for multi-platform have also been studied [21], including embedded sensors capacities, in environments containing obstacles.…”

Section: A Applications Of Multi-uav Systemsmentioning

confidence: 99%

A Mobility Model Based on Improved Artificial Potential Fields for Swarms of UAVs

Falomir

Chaumette

Guerrini

2018

2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

View full text Add to dashboard Cite

A combination of several autonomous UAVs can be used to perform collaborative tasks. Such a combination is referred to as a swarm of drones. The use of multiple platforms can extend the system global capacities thanks to the resulting variety of embedded sensors and to information sharing. In this case, path planning and thus obstacles avoidance is still a major task. To deal with this issue, mobility models have to be implemented. Our contribution presented in this paper is a mobility model for swarms of UAVs based on the Artificial Potential Fields (APF) principle. In our model, the involved UAVs collaborate by sharing data about the obstacles that they detected. By doing so, a UAV which is not close enough to an obstacle to detect it thanks to its own sensors will still have the proper data to take this obstacle into account in its path planning. To validate our mobility strategies with realistic constraints we simulate the performances of existing sensors and transmitters, and consider real-world environment.

show abstract

Section: A Applications Of Multi-uav Systemsmentioning

confidence: 99%

A Mobility Model Based on Improved Artificial Potential Fields for Swarms of UAVs

Falomir

Chaumette

Guerrini

2018

2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

View full text Add to dashboard Cite

show abstract

“…Boskovic et al [7] proposed a six-layered hierarchical architecture, where the problems of real-time mission re-planning, and dynamic agent-to-task assignment were addressed by combining mission planning using evolutionary algorithms, hybrid automata-based task execution and biologically-inspired emergent swarm behaviors.…”

Section: Carlossampedro@upmesmentioning

confidence: 99%

“…In the recent years, and due to its low cost and flexibility, swarm of UAVs have been increasingly investigated [4], [5], [6], [7], [8], [9], [10], [11], and utilized for different type of missions like search and rescue [12], automatic target detection and recognition [6], [13], [14], hunting a target employing multiple UAVs [15], and other highlevel missions that require the coordination between several UAVs to perform the tasks in a faster and more efficient way. Several biologically-inspired approaches and strategies have been proposed for controlling the swarm behavior, such as strategies based on pheromones [6], [4], or using evolutionary algorithms [5], [7], [4].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A flexible and dynamic mission planning architecture for UAV swarm coordination

Sampedro

Bavle

Sánchez-López

et al. 2016

2016 International Conference on Unmanned Aircraft Systems (ICUAS)

View full text Add to dashboard Cite

Abstract-In this paper a scalable and flexible Architecture for real-time mission planning and dynamic agent-to-task assignment for a swarm of Unmanned Aerial Vehicles (UAV) is presented. The proposed mission planning architecture consists of a Global Mission Planner (GMP) which is responsible of assigning and monitoring different high-level missions through an Agent Mission Planner (AMP), which is in charge of providing and monitoring each task of the mission to each UAV in the swarm. The objective of the proposed architecture is to carry out high-level missions such as autonomous multiagent exploration, automatic target detection and recognition, search and rescue, and other different missions with the ability of dynamically re-adapt the mission in real-time. The proposed architecture has been evaluated in simulation and real indoor flights demonstrating its robustness in different scenarios and its flexibility for real-time mission re-planning and dynamic agent-to-task assignment.

show abstract

“…In their scope, each agent is working independently, and changing any one of the group members may have a vital impact on the output of the entire group. Moreover, they did not consider the case that one task could only be carried out by multiple agents together, although they used the term Boškovic et al 39 Multirobotic system task assignment / role assignment 1. Robot-task-target paring method Simulation studies illustrate system efficacy Cheung et al 28 2.…”

Section: Collaboration Typementioning

confidence: 99%

Adaptive Fuzzy Collaborative Task Assignment for Heterogeneous Multirobot Systems

Zhang

Zhong

Nof

2015

Int. J. Intell. Syst.

View full text Add to dashboard Cite

Heterogeneity in robot model mix is advantageous in emerging and future robotic applications. For instance, in a fully automated industrial package loading and unloading scenario, a variety uncertain types of packages need to be continuously sorted and loaded onto designated trucks. To handle the variation of tasks, multiple types of robots, or heterogeneous robots, are designed in the system. However, in such a collaborative system consisting of heterogeneous robots, ineffective task assignments often lead to bad collaboration and thus poor efficiency. To improve the robot collaboration, we herein define the collaborative task assignment problem and develop a fuzzy collaborative intelligence based algorithm to optimize the assignment plans. Specifically, the collaboration type, the collaboration matrix, and the assignment matrix are defined and the new algorithm for adaptive fuzzy collaborative task assignment relies on intuitionistic fuzzy set theory. An unsorted package loading and unloading tasks by heterogeneous robots is used as a case example to validate the new algorithm. Experiments indicate with statistical significance that the new approach shortens total completion time by 21%, reduces total energy consumption by 23%, and increases loading accuracy by 31%, compared with the traditional static task assignment method commonly practiced. The developed approach can be applied to different emerging collaborative systems to improve systems’ collaborative intelligence.

show abstract

Collaborative Mission Planning & Autonomous Control Technology (CoMPACT) System Employing Swarms of UAVs

Cited by 29 publications

References 7 publications

A Mobility Model Based on Improved Artificial Potential Fields for Swarms of UAVs

A Mobility Model Based on Improved Artificial Potential Fields for Swarms of UAVs

A flexible and dynamic mission planning architecture for UAV swarm coordination

Adaptive Fuzzy Collaborative Task Assignment for Heterogeneous Multirobot Systems

Contact Info

Product

Resources

About