TY - JOUR
T1 - Adaptive heterogeneous multi-robot collaboration from formal task specifications
AU - Schillinger, Philipp
AU - García, Sergio
AU - Makris, Alexandros
AU - Roditakis, Konstantinos
AU - Logothetis, Michalis
AU - Alevizos, Konstantinos
AU - Ren, Wei
AU - Tajvar, Pouria
AU - Pelliccione, Patrizio
AU - Argyros, Antonis
AU - Kyriakopoulos, Kostas J.
AU - Dimarogonas, Dimos V.
N1 - Publisher Copyright:
© 2021 Elsevier B.V.
PY - 2021/11
Y1 - 2021/11
N2 - Efficiently coordinating different types of robots is an important enabler for many commercial and industrial automation tasks. Here, we present a distributed framework that enables a team of heterogeneous robots to dynamically generate actions from a common, user-defined goal specification. In particular, we discuss the integration of various robotic capabilities into a common task allocation and planning formalism, as well as the specification of expressive, temporally-extended goals by non-expert users. Models for task allocation and execution both consider non-deterministic outcomes of actions and thus, are suitable for a wide range of real-world tasks including formally specified reactions to online observations. One main focus of our paper is to evaluate the framework and its integration of software modules through a number of experiments. These experiments comprise industry-inspired scenarios as motivated by future real-world applications. Finally, we discuss the results and learnings for motivating practically relevant, future research questions.
AB - Efficiently coordinating different types of robots is an important enabler for many commercial and industrial automation tasks. Here, we present a distributed framework that enables a team of heterogeneous robots to dynamically generate actions from a common, user-defined goal specification. In particular, we discuss the integration of various robotic capabilities into a common task allocation and planning formalism, as well as the specification of expressive, temporally-extended goals by non-expert users. Models for task allocation and execution both consider non-deterministic outcomes of actions and thus, are suitable for a wide range of real-world tasks including formally specified reactions to online observations. One main focus of our paper is to evaluate the framework and its integration of software modules through a number of experiments. These experiments comprise industry-inspired scenarios as motivated by future real-world applications. Finally, we discuss the results and learnings for motivating practically relevant, future research questions.
KW - Abstraction
KW - HRI
KW - Heterogeneous robots
KW - Multi-robot
KW - Robotics
KW - Task allocation
KW - Task decomposition
KW - Temporal logic
UR - http://www.scopus.com/inward/record.url?scp=85113387921&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85113387921&partnerID=8YFLogxK
U2 - 10.1016/j.robot.2021.103866
DO - 10.1016/j.robot.2021.103866
M3 - Article
AN - SCOPUS:85113387921
SN - 0921-8890
VL - 145
JO - Robotics and Autonomous Systems
JF - Robotics and Autonomous Systems
M1 - 103866
ER -