Robust Trajectory Execution for Multi-robot Teams Using Distributed Real-time Replanning
Robust Trajectory Execution for Multi-robot Teams Using Distributed Real-time Replanning
复制标题
使用分布式实时重新规划的多机器人团队的鲁棒轨迹执行
DOI：
10.1007/978-3-030-05816-6_12
复制
发表时间：
2018
期刊：
影响因子：
--
通讯作者：
Ayanian, Nora
中科院分区：
文献类型：
--
作者：
Şenbaşlar, Baskın;Hönig, Wolfgang;Ayanian, Nora
稳健的轨迹执行是合作避碰的扩展，它直接考虑了预先计划的轨迹。我们提出了一种稳健的轨迹执行算法，可以补偿各种动态变化，包括新出现的障碍物、机器人故障、不完美的运动执行和外部干扰。机器人之间不相互通信，只感知其他机器人的位置和周围的障碍物。在高层，我们使用了一种混合规划策略，该策略采用了离散规划和轨迹优化，并采用了动态滚动时间法。离散计划器有助于避免局部极小值，调整计划范围，并为优化阶段提供良好的初始猜测。轨迹优化使用二次规划公式，其中所有安全关键部件都被表示为硬约束。在低层，我们使用缓冲的Voronoi单元作为多机器人的碰撞避免策略。与ORCA相比，我们的方法支持高阶动态限制，更好地避免了死锁。我们在仿真和物理机器人上演示了我们的方法，表明它可以实时操作。
Robust trajectory execution is an extension of cooperative collision avoidance that takes pre-planned trajectories directly into account. We propose an algorithm for robust trajectory execution that compensates for a variety of dynamic changes, including newly appearing obstacles, robots breaking down, imperfect motion execution, and external disturbances. Robots do not communicate with each other and only sense other robots’ positions and the obstacles around them. At the high-level we use a hybrid planning strategy employing both discrete planning and trajectory optimization with a dynamic receding horizon approach. The discrete planner helps to avoid local minima, adjusts the planning horizon, and provides good initial guesses for the optimization stage. Trajectory optimization uses a quadratic programming formulation, where all safety-critical parts are formulated as hard constraints. At the low-level, we use buffered Voronoi cells as a multi-robot collision avoidance strategy. Compared to ORCA, our approach supports higher-order dynamic limits and avoids deadlocks better. We demonstrate our approach in simulation and on physical robots, showing that it can operate in real time.
影响因子：
3.5
作者：
Hornung, Armin;Wurm, Kai M.;Burgard, Wolfram
通讯作者：
Burgard, Wolfram
异构机器人团队的轨迹规划
DOI：
--
发表时间：
2018
期刊：
IEEE/RJS International Conference on Intelligent RObots and Systems
影响因子：
--
作者：
Mark J. Debord;W. Hönig;Nora Ayanian
通讯作者：
Nora Ayanian