<p><b>−</b>Avoiding aerial threats is a significant challenge for Unmanned Ground Vehicles (UGVs), and the uncertainty of dynamic environments further complicates and intensifies the difficulty of evading such threats. To enhance the survivability of UGVs in scenarios where ground-air coupled three-dimensional threats are present, this paper proposes an obstacle avoidance method that solves for the optimal trajectory in dynamic environments. Initially, based on the dynamic motion characteristics of aerial threat targets, the landing points of these threats are predicted. Concurrently, by integrating the state estimation of dynamic obstacles, the environmental safety boundaries are constructed. On this foundation, by considering the safety constraints of obstacle avoidance and the kinematic and dynamic constraints of the vehicle, a local trajectory planning strategy based on dynamic sampling windows is established, and a trajectory evaluation function is proposed to solve for the local optimal trajectory in the current environment. Finally, the effectiveness of the proposed solution is verified through simulation experiments. The proposed solution enables UGVs to perform emergency obstacle avoidance while ensuring vehicle stability when faced with sudden aerial threats, providing a promising solution for effective aerial threat evasion in complex environments.</p>

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Emergency Obstacle Avoidance of Autonomous Vehicles Under Aerial Threats

  • Xiaole Chen,
  • Meijing Wang,
  • Da Jiang,
  • Yinghao Wu,
  • Ling Du,
  • Xiaoming Liang,
  • Hongchao Zhang

摘要

Avoiding aerial threats is a significant challenge for Unmanned Ground Vehicles (UGVs), and the uncertainty of dynamic environments further complicates and intensifies the difficulty of evading such threats. To enhance the survivability of UGVs in scenarios where ground-air coupled three-dimensional threats are present, this paper proposes an obstacle avoidance method that solves for the optimal trajectory in dynamic environments. Initially, based on the dynamic motion characteristics of aerial threat targets, the landing points of these threats are predicted. Concurrently, by integrating the state estimation of dynamic obstacles, the environmental safety boundaries are constructed. On this foundation, by considering the safety constraints of obstacle avoidance and the kinematic and dynamic constraints of the vehicle, a local trajectory planning strategy based on dynamic sampling windows is established, and a trajectory evaluation function is proposed to solve for the local optimal trajectory in the current environment. Finally, the effectiveness of the proposed solution is verified through simulation experiments. The proposed solution enables UGVs to perform emergency obstacle avoidance while ensuring vehicle stability when faced with sudden aerial threats, providing a promising solution for effective aerial threat evasion in complex environments.