We present Topology-Guided ORCA as an alternative simulator to replace ORCA for planning smooth multi-agent motions in environments with static obstacles. Despite the impressive performance in simulating multi-agent crowd motion in free space, ORCA encounters a significant challenge in navigating the agents with the presence of static obstacles. ORCA ignores static obstacles until an agent gets too close to an obstacle, and the agent will get stuck if the obstacle intercepts an agent's path toward the goal. To address this challenge, Topology-Guided ORCA constructs a graph to represent the topology of the traversable region of the environment. We use a path planner to plan a path of waypoints that connects each agent's start and goal positions. The waypoints are used as a sequence of goals to guide ORCA. The experiments of crowd simulation in constrained environments show that our method outperforms ORCA in terms of generating smooth and natural motions of multiple agents in constrained environments, which indicates great potential of Topology-Guided ORCA for serving as an effective simulator for training constrained social navigation policies.

翻译：本文提出拓扑引导ORCA作为替代ORCA的仿真器，用于在存在静态障碍物的环境中规划平滑的多智能体运动。尽管ORCA在自由空间多智能体人群运动仿真中表现出色，但在存在静态障碍物的导航场景中面临重大挑战。ORCA会忽略静态障碍物直至智能体过于接近障碍物，且当障碍物阻挡智能体通往目标的路径时，智能体会陷入停滞。为解决此问题，拓扑引导ORCA构建图结构以表征环境可通行区域的拓扑特征。我们采用路径规划器为每个智能体的起点与目标位置规划由航点构成的路径，并将这些航点作为目标序列来引导ORCA。受限环境下的人群仿真实验表明，本方法在生成受限环境中多智能体平滑自然运动方面优于ORCA，这预示着拓扑引导ORCA作为训练受限社会导航策略的有效仿真器具有巨大潜力。