We propose factor graph optimization for simultaneous planning, control, and trajectory estimation for collision-free navigation of autonomous systems in environments with moving objects. The proposed online probabilistic motion planning and trajectory estimation navigation technique generates optimal collision-free state and control trajectories for autonomous vehicles when the obstacle motion model is both unknown and known. We evaluate the utility of the algorithm to support future autonomous robotic space missions.
翻译:我们建议对自动系统在有移动物体的环境中的无碰撞导航同时进行规划、控制和轨迹估计的因数图形优化。 拟议的在线概率运动规划和轨迹估计导航技术在障碍运动模式既未知又已知的情况下,为自动车辆带来最佳的无碰撞状态和控制轨道。 我们评估了算法对支持未来自主机器人空间飞行任务的效用。