Collision-free mobile robot navigation is an important problem for many robotics applications, especially in cluttered environments. In such environments, obstacles can be static or dynamic. Dynamic obstacles can additionally be interactive, i.e. changing their behavior according to the behavior of other entities. The perception and prediction modules of robotic systems create probabilistic representations and predictions of such environments. In this paper, we propose a novel prediction representation for interactive behaviors of dynamic obstacles. Then, we propose a real-time trajectory planning algorithm that probabilistically avoids collisions against static and interactive dynamic obstacles, and produces dynamically feasible trajectories. During decision making, our planner simulates the interactive behavior of dynamic obstacles in response to the actions planning robot takes. We explicitly minimize collision probabilities against static and dynamic obstacles using a multi-objective search formulation. Then, we formulate a quadratic program to safely fit a smooth trajectory to the search result while attempting to preserve the collision probabilities computed during search. We evaluate our algorithm extensively in simulations to show its performance under different environments and configurations using 78000 randomly generated cases. We compare its performance to a state-of-the-art trajectory planning algorithm for static and dynamic obstacle avoidance using 4500 randomly generated cases. We show that our algorithm achieves up to 3.8x success rate using as low as 0.18x time the baseline uses. We implement our algorithm for physical quadrotors, and show its feasibility in the real world.

翻译：无碰撞移动机器人导航是诸多机器人应用中的重要问题，尤其在杂乱环境中尤为突出。此类环境中的障碍物可分为静态与动态两类，其中动态障碍物可能具有交互性，即其行为会根据其他实体的行为发生改变。机器人系统的感知与预测模块会生成此类环境的概率化表征与预测。本文首先提出一种新型的交互式动态障碍物行为预测表征，进而设计一种实时轨迹规划算法，该算法能够概率性避开静态与交互式动态障碍物，并生成动态可行的轨迹。在决策过程中，我们的规划器会模拟动态障碍物对规划机器人动作的交互反应，通过多目标搜索方案显式最小化与静态及动态障碍物的碰撞概率。随后，我们构建二次规划模型，在尽可能保留搜索阶段碰撞概率的前提下，将平滑轨迹安全拟合至搜索结果。通过78000个随机生成案例，我们在仿真环境中系统评估了该算法在不同环境与配置下的性能表现，并与采用4500个随机生成案例的当前最先进静动态障碍物避障轨迹规划算法进行对比。结果表明，本算法成功率达基准算法的3.8倍，而运行时间仅为其0.18倍。最后，我们在实体四旋翼飞行器上实现该算法，验证了其在真实环境中的可行性。