Probabilistic multi-robot planning with temporal tasks and communication constraints

Multi-robot systems are broadly used in applications such as search and rescue, environmental monitoring, and mapping of unknown environments. Effective coordination among these robots often relies on distributed information and local decision-making. However, maintaining constant communication links between robots can be challenging due to environmental and task constraints. Robots can move around to seek temporal communication links that over time jointly establish the intermittent connectivity of the network. This paper aims to incorporate temporal communication constraints into the path planning for multi-robot teams with stochastic motion and handling complex tasks specified in a temporal order. We use formal methods to model the temporal specification of tasks. Task assignments and high-level communication requirements are provided to individual robots on a multi-robot team as independent temporal logic expressions. Robots update their plans for future communication events according to their local decision-making algorithms and jointly synthesize a bottom-up policy to meet the communication requirements. We provide a strategyto maintain intermittent connectivity while satisfying a risk constraint.In addition, we systematically analyze the impact of different rendezvous selection strategies, comparing cost functions that minimize the total traveled distance, balance distances among robots, or incorporate risk awareness. Our simulation results suggest that the proposed method effectively accommodates diverse operational preferences, enhancing flexibility, robustness, and overall mission performance.

In this paper, we develop a distributed intermittent communication and task planning framework for mobile robot teams. The goal of the robots is to accomplish complex tasks, captured by local linear temporal logic formulas, and share the collected information with all other robots and possibly also with a user. Specifically, we consider situations where the robot communication capabilities are not sufficient to form reliable and connected networks, while the robots move to accomplish their tasks. In this case, intermittent communication protocols are necessary that allow the robots to temporarily disconnect from the network in order to accomplish their tasks free of communication constraints. We assume that the robots can only communicate with each other when they meet at common locations in space. Our distributed control framework jointly determines local plans that allow all robots to fulfill their assigned temporal tasks, sequences of communication events that guarantee information exchange infinitely often, and optimal communication locations that minimize a desired distance metric. Simulation results verify the efficacy of the proposed controllers.