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

Abstract

Abstract-We present an efficient approach to plan action sequences for a team of robots from a single finite LTL mission specification. The resulting execution strategy is proven to solve the given mission with minimal team costs, e.g., with shortest execution time. For planning, an established graphbased search method based on the multi-objective shortest path problem is adapted to multi-robot planning and extended to support resource constraints. We further improve planning efficiency significantly for missions which consist of independent parts by using previous results regarding LTL decomposition. The efficiency and practicality of the ROS implementation of our approach is demonstrated in example scenarios.

Auctioning over Probabilistic Options for Temporal Logic-Based Multi-Robot Cooperation Under Uncertainty

“…[18] also assumes pre-assigned tasks, but considers uncertainty in advance and clusters the robots into teams. In [23], we automatically identify independent tasks and also optimize allocation, but do not consider uncertainty.…”

“…Linear Temporal Logic (LTL) [2], including its fragment co-safe LTL [11], is an established formalism to express such specifications. It is well understood how provably correct action plans can be derived from LTL specifications [3,23].…”

Simultaneous task allocation and planning for temporal logic goals in heterogeneous multi-robot systems

“…Third, by modeling costs as the required execution time, the goal is to minimize the maximum of agent costs instead of their sum as in most of the existing approaches. This can be addressed by multi-objective optimization, see for example Gandibleux et al (2006) or Paixão and Santos (2013), where the cost of each agent is considered as one objective as proposed in our previous work Schillinger et al (2017).…”

“…This extends our approach presented here to cases where no set of independent tasks is defined explicitly. Furthermore, we extend our approach in Schillinger et al (2017) on resource-constrained multi-agent planning to utilize the specific structure of the team model and to support resource constraints as part of the LTL specification.…”

System Design for Coordinated Multi-robot Assistance Deployment in Smart Spaces

“…Human teaming with robots has been considered in applica- tions ranging from Urban Search and Rescue (USAR) [13], coproduction [10], more recently in scenarios related to AAL for people with reduced mobility [30], [8] and finally in general purpose scenarios [22]. AAL scenarios add another level of complexity because the end-users are not professional experts trained to use the underlying technology while there can be additional humans of different roles being involved aside the end-users (such as doctors, service personnel, etc).…”