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| Main Authors: | , , |
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| Format: | Preprint |
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2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2605.24865 |
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| _version_ | 1866917528883691520 |
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| author | Pradhan, Prateek Priyaranjan Rajawat, Ketan Kothari, Mangal |
| author_facet | Pradhan, Prateek Priyaranjan Rajawat, Ketan Kothari, Mangal |
| contents | Communication-aware trajectory generation for unmanned aerial vehicles (UAVs) operating in urban environments requires simultaneous consideration of vehicle dynamics, wireless communication quality, obstacle avoidance, and onboard energy limitations. In such missions, UAVs must navigate through obstacle-rich environments while ensuring reliable relay of mission-critical sensory information to ground infrastructure. This results in a highly nonlinear and nonconvex optimal control problem involving coupled communication and flight-dynamics constraints. This paper presents a communication-constrained energy-optimal trajectory generation framework for quadrotor UAVs operating in urban environments. The proposed formulation incorporates full rigid-body quadrotor dynamics, urban wireless communication models, cumulative data throughput constraints, and obstacle avoidance requirements within a unified free-final-time optimal control framework. Unlike conventional approaches based on simplified kinematic or point-mass models, the proposed framework generates dynamically feasible trajectories suitable for practical aerial platforms. The resulting nonconvex optimal control problem is solved iteratively using sequential convex programming (SCP). Numerical simulations for multiple urban mission scenarios demonstrate the ability of the proposed framework to generate energy-efficient and communication-aware trajectories while adapting mission duration according to data relay requirements. The proposed methodology provides a practical framework for autonomous UAV operations requiring reliable communication in dense urban environments. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_24865 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Communication-Constrained Energy-Optimal Trajectory Generation for Quadrotor UAVs in Urban Environments Pradhan, Prateek Priyaranjan Rajawat, Ketan Kothari, Mangal Systems and Control Communication-aware trajectory generation for unmanned aerial vehicles (UAVs) operating in urban environments requires simultaneous consideration of vehicle dynamics, wireless communication quality, obstacle avoidance, and onboard energy limitations. In such missions, UAVs must navigate through obstacle-rich environments while ensuring reliable relay of mission-critical sensory information to ground infrastructure. This results in a highly nonlinear and nonconvex optimal control problem involving coupled communication and flight-dynamics constraints. This paper presents a communication-constrained energy-optimal trajectory generation framework for quadrotor UAVs operating in urban environments. The proposed formulation incorporates full rigid-body quadrotor dynamics, urban wireless communication models, cumulative data throughput constraints, and obstacle avoidance requirements within a unified free-final-time optimal control framework. Unlike conventional approaches based on simplified kinematic or point-mass models, the proposed framework generates dynamically feasible trajectories suitable for practical aerial platforms. The resulting nonconvex optimal control problem is solved iteratively using sequential convex programming (SCP). Numerical simulations for multiple urban mission scenarios demonstrate the ability of the proposed framework to generate energy-efficient and communication-aware trajectories while adapting mission duration according to data relay requirements. The proposed methodology provides a practical framework for autonomous UAV operations requiring reliable communication in dense urban environments. |
| title | Communication-Constrained Energy-Optimal Trajectory Generation for Quadrotor UAVs in Urban Environments |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2605.24865 |