Architecture for Complex Collaborative Multi-Robot Systems
This study presents a 6-layer architecture designed to enable multiple robots to collaborate effectively on various missions. The architecture includes layers for individual robot functionalities, team management, mission oversight, system monitoring, human-agent interaction, and user interface. Each layer plays a crucial role in ensuring flexibility, adaptability, and successful coordination among the robots in dynamic environments. The proposed architecture addresses the challenges of new missions, team formation, environmental changes, and human supervision, providing a comprehensive framework for real-world deployment.
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Presentation Transcript
Multiple Robots For Multiple Missions: Architecture for Complex Collaboration ARIEL ROSENFELD2 2, NOA AGMON1, OLEG MAKSIMOV1, ARIEL ROSENFELD SHAI SHLOMAI1, SARIT KRAUS1 1BAR-ILAN UNIVERSITY, ISRAEL 2WEIZMANN INSTITUTE OF SCIENCE, ISRAEL AGA WORKSHOP @ IJCAI 2017
What do you want from us? Multi-robot systems require flexibility. New missions Form new teams React to environment changes and failures (e.g., communication) Human supervisor Etc. No existing architecture is able to handle all of the above in real deployment. We propose a 6-layer architecture and empirically evaluate it. AGA WORKSHOP @ IJCAI 2017
Team Patrol Demonstration.mp4 AGA WORKSHOP @ IJCAI 2017
Layer 1 - Robots Each robot has built-in functionalities. Rotate wheels 20 degrees left Navigate to GPS coordinates (x,y,z). Etc. Each robot is semi-autonomous. AGA WORKSHOP @ IJCAI 2017
Layer 2 Team Manager Robots may be clustered into teams which in turn can be clustered into teams which . The team manager manages a group. Allows inter-team communication Represents the group s state Etc. AGA WORKSHOP @ IJCAI 2017
Layer 3 Mission Manager Oversees a mission. Creates PLANS for the subordinate teams. The Plans are overseen by the team manager(s) which report to the MM. AGA WORKSHOP @ IJCAI 2017
Layer 4 System Manager Monitors and creates all Missions Resources Etc. Usually, centralized?. AGA WORKSHOP @ IJCAI 2017
Layer 5 Supporting agent Information filtering and prioritization for the human operator. Smart buffer between the system manager and the human operator(s) MOVIE! Rosenfeld et al. Intelligent Agent Supporting Human- Multi-Robot Team Collaboration, IJCAI 2015 (AIJ 2017) AGA WORKSHOP @ IJCAI 2017
Layer 6 UI AGA WORKSHOP @ IJCAI 2017
Evaluation PLACE ROBOTS Outdoor environment (two basketball courts). A total 25x25 meters. The system consisted of four Hamster robots. Each is semi-autonomous robot, that cooperates according to the architecture described below. SCENARIO The operator decides to execute a patrolling task, and defines the waypoints for the mission. Then, communication problems occur. AGA WORKSHOP @ IJCAI 2017
MOVIE AGA WORKSHOP @ IJCAI 2017
Results Idleness = time between two visits to a patrol point. Sync = overhead AGA WORKSHOP @ IJCAI 2017
Results 2 - Simulation Increasing the size of the patrol by 2.5, 5 and 10. Examined 15 and 20 robots patrolling. Good scalability in environment size AGA WORKSHOP @ IJCAI 2017
Summary New Architecture. Allows ample flexibility and resilience. Empirical evaluation support that. All code is available online: www.tinyurl.com/MRMM-IJCAI AGA WORKSHOP @ IJCAI 2017
Thanks Ariel Rosenfeld All code is available online: www.tinyurl.com/MRMM-IJCAI www.arielrosenfeld.com Noa Agmon, Oleg Maximov, Ariel Rosenfeld, Shai Shlomai, Sarit Kraus Multiple Robots For Multiple Missions: Architecture for Complex Collaboration AGA WORKSHOP @ IJCAI 2017
