Trajectory and control secrecy is an important issue in robotics security. This paper proposes a novel algorithm for the control input inference of a mobile agent without knowing its control objective. Specifically, the algorithm first estimates the target state by applying external perturbations. Then we identify the objective function based on the inverse optimal control, providing the well-posedness proof and the identifiability analysis. Next, we obtain the optimal estimate of the control horizon using binary search. Finally, the agent's control optimization problem is reconstructed and solved to predict its input. Simulation illustrates the efficiency and the performance of the algorithm.

翻译：轨迹与控制保密性是机器人安全领域的重要问题。本文提出了一种新颖算法，用于在未知控制目标的情况下推断移动智能体的控制输入。具体而言，该算法首先通过施加外部扰动来估计目标状态，然后基于逆最优控制识别目标函数，并给出了适定性证明与可辨识性分析。接着，采用二分法搜索获取控制时域的最优估计，最终重构并求解智能体的控制优化问题以预测其输入。仿真结果验证了该算法的有效性与性能。