Decomposition of Finite LTL Specifications for Efficient Multi-agent Planning

Abstract

Generating verifiably correct execution strategies from Linear Temporal Logic (LTL) mission specifications avoids the need for manually designed robot behaviors. However, when incorporating a team of robot agents, the additional model complexity becomes a critical issue. Given a single finite LTL mission and a team of robots, we propose an automata-based approach to automatically identify possible decompositions of the LTL specification into sets of independently executable task specifications. Our approach leads directly to the construction of a team model with significantly lower complexity than other representations constructed with conventional methods. Thus, it enables efficient search for an optimal decomposition and allocation of tasks to the robot agents.

Reactive mission and motion planning with deadlock resolution avoiding dynamic obstacles

“…Distributed and decomposition-based planning approaches tackle the complexity problem when scaling to a large number of robots. For instance, Tumova and Dimarogonas (2015) construct distributed controllers from a specifications already separated into coordinating and non-coordinating tasks, while Schillinger et al (2016) automatically decompose a specification into independent, distributed task specifications. In most approaches, moving obstacles are modeled in a discrete manner as part of the abstraction, leading to over-conservative restrictions like requiring robots to be at least one region apart.…”

Multi-objective search for optimal multi-robot planning with finite LTL specifications and resource constraints

“…Since this means that the state space is exponential in N , this approach is only feasible for small team sizes. An alternative team model representation was proposed in [8] which is linear in N . We recall this representation in Section V and discuss implications for the presented planning approach, although the general planning algorithm can be used for any construction of a team model C.…”

“…Our previous work [8] addresses the case that a mission implicitly consists of multiple independent parts, called tasks T i . Instead of requiring to manually declare such tasks, it presents a way to identify them based on the single given LTL mission specification M. As summarized in the first part of this section, this enables the construction of a special team model with its state space linear in the number agents.…”

“…To reduce complexity, [7] abstracts from independent motions of the single agents. In previous work [8], we proposed a way to identify independent parts of a finite LTL mission. The named approaches focus on LTL constraints, which are discrete in nature.…”

“…(2) By extending Martins' algorithm, we propose an efficient algorithm to solve this planning problem in Section IV. (3) As a special case of representing a team, we build upon our previous results of identifying independent parts of a mission [8] and outline an adaptation in Section V to improve efficiency for decomposable missions. (4) We present a case study of our ROS implementation in Section VI and discuss it for variations of an example mission.…”