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| Title: | Cooperative UAV formation flying with obstacle/collision avoidance | |
| Author (s): | Wang, Xiaohua Yadav, V. Balakrishnan, S. N. | |
| Department/Lab Affiliations: | Mechanical & Aerospace Engineering Space Systems Engineering | |
| Keywords: | aircraft control collision avoidance geometry mobile robots navigation neurocontrollers predictive control remotely operated vehicles tracking | |
| Issue Date: | 2007 | |
| Publisher: | Institute of Electrical and Electronics Engineers IEEE | |
| Citation: | Wang, Xiaohua Yadav,V. and Balakrishnan,S.N. “Cooperative UAV Formation Flying with Obstacle/Collision Avoidance”, IEEE Transactions on Control Systems Technology, Vol. 15,no.4, 2007, pp. 672-679, 2007 | |
| Abstract: | Navigation problems of unmanned air vehicles (UAVs) flying in a formation in a free and an obstacle-laden environment are investigated in this brief. When static obstacles popup during the flight, the UAVs are required to steer around them and also avoid collisions between each other. In order to achieve these goals, a new dual-mode control strategy is proposed: a "safe mode" is defined as an operation in an obstacle-free environment and a "danger mode" is activated when there is a chance of collision or when there are obstacles in the path. Safe mode achieves global optimization because the dynamics of all the UAVs participating in the formation are taken into account in the controller formulation. In the danger mode, a novel algorithm using a modified Grossberg neural network (GNN) is proposed for obstacle/collision avoidance. This decentralized algorithm in 2-D uses the geometry of the flight space to generate optimal/suboptimal trajectories. Extension of the proposed scheme for obstacle avoidance in a 3-D environment is shown. In order to handle practical vehicle constraints, a model predictive control-based tracking controller is used to track the references generated. Numerical results are provided to motivate this approach and to demonstrate its potential. | |
| Type: | Article - Journal text | |
| In Title: | IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY | |
| Copyright Notice: | This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. allows publisher's final version to be uploaded FULL COPYRIGHT INFORMATION: | |
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| title | Cooperative UAV formation flying with obstacle/collision avoidance | |
| contributor.author | Wang, Xiaohua | |
| contributor.author | Yadav, V. | |
| contributor.author | Balakrishnan, S. N. | |
| contributor.deptlab | Mechanical & Aerospace Engineering | |
| contributor.deptlab | Space Systems Engineering | |
| subject | aircraft control | |
| subject | collision avoidance | |
| subject | geometry | |
| subject | mobile robots | |
| subject | navigation | |
| subject | neurocontrollers | |
| subject | predictive control | |
| subject | remotely operated vehicles | |
| subject | tracking | |
| date.issued | 2007 | |
| publisher | Institute of Electrical and Electronics Engineers IEEE | |
| identifier.citation | Wang, Xiaohua Yadav,V. and Balakrishnan,S.N. “Cooperative UAV Formation Flying with Obstacle/Collision Avoidance”, IEEE Transactions on Control Systems Technology, Vol. 15,no.4, 2007, pp. 672-679, 2007 | |
| identifier.pub.URI | ||
| description.abstract | Navigation problems of unmanned air vehicles (UAVs) flying in a formation in a free and an obstacle-laden environment are investigated in this brief. When static obstacles popup during the flight, the UAVs are required to steer around them and also avoid collisions between each other. In order to achieve these goals, a new dual-mode control strategy is proposed: a "safe mode" is defined as an operation in an obstacle-free environment and a "danger mode" is activated when there is a chance of collision or when there are obstacles in the path. Safe mode achieves global optimization because the dynamics of all the UAVs participating in the formation are taken into account in the controller formulation. In the danger mode, a novel algorithm using a modified Grossberg neural network (GNN) is proposed for obstacle/collision avoidance. This decentralized algorithm in 2-D uses the geometry of the flight space to generate optimal/suboptimal trajectories. Extension of the proposed scheme for obstacle avoidance in a 3-D environment is shown. In order to handle practical vehicle constraints, a model predictive control-based tracking controller is used to track the references generated. Numerical results are provided to motivate this approach and to demonstrate its potential. | |
| type | Article - Journal | |
| type.DCMIType | text | |
| type.status | Final version | |
| rights | This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. | |
| rights | allows publisher's final version to be uploaded | |
| rights.URI | ||
| rights.URI | ||
| rights.URI | ||
| relation.isPartOf | IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY | |
| date.accessioned | 2008-09-11T13:34:47Z | |
| date.available | 2008-09-17T21:03:00Z | |
| identifier.persist.URI | ||
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