Combining symbolic and geometric reasoning in multi-agent systems is a
challenging task that involves planning, scheduling, and synchronization
problems. Existing works overlooked the variability of task duration and
geometric feasibility that is intrinsic to these systems because of the
interaction between agents and the environment. We propose a combined task and
motion planning approach to optimize sequencing, assignment, and execution of
tasks under temporal and spatial variability. The framework relies on
decoupling tasks and actions, where an action is one possible geometric
realization of a symbolic task. At the task level, timeline-based planning
deals with temporal constraints, duration variability, and synergic assignment
of tasks. At the action level, online motion planning plans for the actual
movements dealing with environmental changes. We demonstrate the approach
effectiveness in a collaborative manufacturing scenario, in which a robotic arm
and a human worker shall assemble a mosaic in the shortest time possible.
Compared with existing works, our approach applies to a broader range of
applications and reduces the execution time of the process.

本文提出了一种联合任务和运动规划方法来优化任务的排序、分配和执行，解决多智能体系统中的时空变异性问题，采用时间轴规划处理任务的时间约束、时间变化和协同分配，在网络平面规划中以环境变化为前提，证明了该方法的有效性。