The Geometric Model Predictive Path Integral (GMPPI) controller is introduced, capable of tracking agile trajectories and avoiding obstacles online by directly using depth sensor data and is a sampling-based predictive control method that considers nonlinear system dynamics and uses a proposed UAV-specific cost function.
Simulation results for a three-UAV swarm in a cluttered environment demonstrate that the proposed distributed NMPC-based trajectory planning method can generate dynamically feasible and collision-free trajectories, while enabling the swarm to reach the assigned target positions and preserve the desired formation within...
Ying-Ting Cui, Tong-Xin Zeng, Bin Li· Drones· 0 citations
Autonomous UAV flight through cluttered and partially unknown environments requires reasoning not only about observed obstacles but also about occluded regions that the sensor cannot observe. We present OA-MPPI, an obstacle- and occlusion-aware extension of Model Predictive Path Integral (MPPI) control for quadrotor fl...
Vittorio Palladino, Teaya Yang, Ruiqi Zhang et al.· 0 citations
Simulation verification shows that the proposed UAV trajectory planning method based on Model Predictive Control dual-model cooperative control can significantly reduce environmental uncertainty, improve trajectory tracking accuracy and active obstacle avoidance ability, and exhibit stronger robustness, decision-making...
Yi-Tong Zhang· European Conference on Elect...· 0 citations
Quadrotor unmanned aerial vehicles (UAVs) have advantages such as simple structure, flexible manipulation, and strong capabilities of vertical takeoff/landing and hovering, thus being widely applied in various complex environments and tasks. However, their short endurance limits the scope of application. The collaborat...
Xiao-Kang Zhu, Teng Fang, Biao Zou et al.· Engineering Reports· 0 citations
We present a learning-based approach to kinodynamic online motion planning for an Unmanned Aerial Vehicle (UAV) operating at a fixed altitude in unknown dynamic environments, where real-time avoidance of both static and dynamic obstacles must be achieved under conditions of extreme partial observability. The UAV is con...
Mohammad Reza Ranjbar Divkoti, A. Aguiar· 0 citations
The proposed path deviation control method significantly improves path accuracy, stability, and obstacle avoidance capability in multi-drone cooperative tasks and can be widely applied in fields such as logistics distribution, disaster monitoring, and cooperative inspection.
Jing Liao· Journal of Measurements in E...· 0 citations
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