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| Title: | Neural network approach for obstacle avoidance in 3-D environments for UAVs | |
| Author (s): | Yadav, V. Xiaohua Wang Balakrishnan, S. N. | |
| Department/Lab Affiliations: | Mechanical & Aerospace Engineering | |
| Keywords: | aerospace control collision avoidance control engineering computing controller design model predictive control based controller neural nets obstacle avoidance obstacle free trajectories predictive control remotely operated vehicles unmanned air vehicles vision-inspired Grossberg neural network | |
| Issue Date: | 2006 | |
| Publisher: | Institute of Electrical and Electronics Engineers | |
| Citation: | Yadav, V.; Xiaohua Wang; Balakrishnan, S. N. "Neural network a pp.oach for obstacle avoidance in 3-D environments for UAVs" American Control Conference, 2006, 14-16 June 2006 Pages: 6 | |
| Abstract: | In this paper a controller design is proposed to get obstacle free trajectories in a three dimensional urban environment for unmanned air vehicles (UAVs). The controller has a two-layer architecture. In the upper layer, vision-inspired Grossberg neural network is proposed to get the shortest distance paths. In the bottom layer, a model predictive control (MPC) based controller is used to obtain dynamically feasible trajectories. Simulation results are presented for to demonstrate the potential of the approach. | |
| Type: | Article - Conference proceedings text | |
| 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. FULL COPYRIGHT INFORMATION: | |
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| title | Neural network approach for obstacle avoidance in 3-D environments for UAVs | |
| contributor.author | Yadav, V. | |
| contributor.author | Xiaohua Wang | |
| contributor.author | Balakrishnan, S. N. | |
| contributor.deptlab | Mechanical & Aerospace Engineering | |
| subject | aerospace control | |
| subject | collision avoidance | |
| subject | control engineering computing | |
| subject | controller design | |
| subject | model predictive control based controller | |
| subject | neural nets | |
| subject | obstacle avoidance | |
| subject | obstacle free trajectories | |
| subject | predictive control | |
| subject | remotely operated vehicles | |
| subject | unmanned air vehicles | |
| subject | vision-inspired Grossberg neural network | |
| date.issued | 2006 | |
| date.submitted | 2007 | |
| publisher | Institute of Electrical and Electronics Engineers | |
| identifier.citation | Yadav, V.; Xiaohua Wang; Balakrishnan, S. N. "Neural network a pp.oach for obstacle avoidance in 3-D environments for UAVs" American Control Conference, 2006, 14-16 June 2006 Pages: 6 | |
| identifier.pub.URI | ||
| description.abstract | In this paper a controller design is proposed to get obstacle free trajectories in a three dimensional urban environment for unmanned air vehicles (UAVs). The controller has a two-layer architecture. In the upper layer, vision-inspired Grossberg neural network is proposed to get the shortest distance paths. In the bottom layer, a model predictive control (MPC) based controller is used to obtain dynamically feasible trajectories. Simulation results are presented for to demonstrate the potential of the approach. | |
| type | Article - Conference proceedings | |
| 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.URI | ||
| date.accessioned | 2007-04-05T14:27:14Z | |
| date.available | 2007-04-05T14:27:14Z | |
| identifier.persist.URI | ||
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