Cascade-type guidance law design for multiple-UAV formation keeping

No, Tae Soo; Kim, Youdan; Tahk, Min-Jea; Jeon, Gyeong-Eon

doi:10.1016/j.ast.2010.08.011

Cited by 41 publications

(25 citation statements)

References 14 publications

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“…The research endeavor in the formation driving community is aimed mainly at tasks of formation stabilization [3], [4], [5], [6], [7] and/or formation following a predefined path [8], [4], [9], [10], [11]. The algorithms are designed for UGV formations [3], [8], for unmanned vehicle (UAV) formations [4], [11], for MAV (mainly quadrotors) formations [9], [10], [6], [7] or even for heterogeneous MAV-UGV formations [5].…”

mentioning

confidence: 99%

Navigation, localization and stabilization of formations of unmanned aerial and ground vehicles

Saska

Krajník

Vonásek

et al. 2013

2013 International Conference on Unmanned Aircraft Systems (ICUAS)

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Abstract-A leader-follower formation driving algorithm developed for control of heterogeneous groups of unmanned micro aerial and ground vehicles stabilized under a top-view relative localization is presented in this paper. The core of the proposed method lies in a novel avoidance function, in which the entire 3D formation is represented by a convex hull projected along a desired path to be followed by the group. Such a representation of the formation provides non-collision trajectories of the robots and respects requirements of the direct visibility between the team members in environment with static as well as dynamic obstacles, which is crucial for the top-view localization. The algorithm is suited for utilization of a simple yet stable visual based navigation of the group (referred to as GeNav), which together with the on-board relative localization enables deployment of large teams of micro-scale robots in environments without any available global localization system. We formulate a novel Model Predictive Control (MPC) based concept that enables to respond to the changing environment and that provides a robust solution with team members' failure tolerance included. The performance of the proposed method is verified by numerical and hardware experiments inspired by reconnaissance and surveillance missions.

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mentioning

confidence: 99%

Navigation, localization and stabilization of formations of unmanned aerial and ground vehicles

Saska

Krajník

Vonásek

et al. 2013

2013 International Conference on Unmanned Aircraft Systems (ICUAS)

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“…We do not rely on following a given trajectory, as in most of the state-of-the-art methods [45], [46], [47]. We propose to integrate the stabilization of followers in the desired positions behind the leader together with the trajectory planning into a desired goal area with obstacle avoidance ability for the entire formation.…”

Section: Multi-robot Scenarios Demonstrating the Practical Usabilmentioning

confidence: 99%

System for deployment of groups of unmanned micro aerial vehicles in GPS-denied environments using onboard visual relative localization

et al. 2016

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Abstract-A complex system for control of swarms of Micro Aerial Vehicles (MAV), in literature also called as Unmanned Aerial Vehicles (UAV) or Unmanned Aerial Systems (UAS), stabilized via an onboard visual relative localization is described in this paper. The main purpose of this work is to verify the possibility of self-stabilization of multi-MAV groups without an external global positioning system. This approach enables the deployment of MAV swarms outside laboratory conditions, and it may be considered an enabling technique for utilizing fleets of MAVs in real-world scenarios. The proposed visualbased stabilization approach has been designed for numerous different multi-UAV robotic applications (leader-follower UAV formation stabilization, UAV swarm stabilization and deployment in surveillance scenarios, cooperative UAV sensory measurement) in this paper. Deployment of the system in real-world scenarios truthfully verifies its operational constraints, given by limited onboard sensing suites and processing capabilities. The performance of the presented approach (MAV control, motion planning, MAV stabilization, and trajectory planning) in multi-MAV applications has been validated by experimental results in indoor as well as in challenging outdoor environments (e.g., in windy conditions and in a former pit mine).

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“…The above mentioned techniques are suited for utilization of robots under a precise external global localization system (for example approaches [13] are verified with the VICON system), for UGV formations they often rely on a dead reckoning with its cumulative error [8] or they provide theoretical solutions verified only by simulations [4], [5], [7], [9], [10], [11], [12], [14], where a known position of robots may be assumed. In our work, the necessity of utilization of on-board systems for robots' localization and navigation is inherently included in the essence of the formation driving approach.…”

Section: State Of the Artmentioning

confidence: 99%

“…Beside the methods of the formation driving for UGVs, we should mention few approaches designed for UAVs [11], [12], [13], [14]. In [11], the formation stabilization and keeping in the desired shape are treated as a dynamic 3D tracking problem, where the relative geometry of multiple UAVs is kept via a cascade-type guidance low under the leader-follower concept.…”

Section: State Of the Artmentioning

confidence: 99%

“…In [11], the formation stabilization and keeping in the desired shape are treated as a dynamic 3D tracking problem, where the relative geometry of multiple UAVs is kept via a cascade-type guidance low under the leader-follower concept. A leader-follower approach for stabilization of helicopter's formations using a nonlinear model predictive control is proposed in [12] and optimized for on-line embedded solution enabling a response to the fast dynamic of UAVs in [13].…”

Section: State Of the Artmentioning

confidence: 99%

See 1 more Smart Citation

Fault-Tolerant Formation Driving Mechanism Designed for Heterogeneous MAVs-UGVs Groups

Saska

Krajník

Vonásek

et al. 2013

J Intell Robot Syst

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Cascade-type guidance law design for multiple-UAV formation keeping

Cited by 41 publications

References 14 publications

Navigation, localization and stabilization of formations of unmanned aerial and ground vehicles

Navigation, localization and stabilization of formations of unmanned aerial and ground vehicles

System for deployment of groups of unmanned micro aerial vehicles in GPS-denied environments using onboard visual relative localization

Fault-Tolerant Formation Driving Mechanism Designed for Heterogeneous MAVs-UGVs Groups

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