From Design to Deployment: Decentralized Coordination of Heterogeneous Robotic Teams

Abstract

Many applications benefit from the use of multiple robots, but their scalability and applicability are fundamentally limited when relying on a central control station. Getting beyond the centralized approach can increase the complexity of the embedded software, the sensitivity to the network topology, and render the deployment on physical devices tedious and error-prone. This work introduces a software-based solution to cope with these challenges on commercial hardware. We bring together our previous work on Buzz, the swarm-oriented programming language, and the many contributions of the Robotic Operating System (ROS) community into a reliable workflow, from rapid prototyping of decentralized behaviors up to robust field deployment. The Buzz programming language is a hardware independent, domain-specific (swarm-oriented), and composable language. From simulation to the field, a Buzz script can stay unmodified and almost seamlessly applicable to all units of a heterogeneous robotic team. We present the software structure of our solution, and the swarm-oriented paradigms it encompasses. While the design of a new behavior can be achieved on a lightweight simulator, we show how our security mechanisms enhance field deployment robustness. In addition, developers can update their scripts in the field using a safe software release mechanism. Integrating Buzz in ROS, adding safety mechanisms and granting field updates are core contributions essential to swarm robotics deployment: from simulation to the field. We show the applicability of our work with the implementation of two practical decentralized scenarios: a robust generic task allocation strategy and an optimized area coverage algorithm. Both behaviors are explained and tested with simulations, then experimented with heterogeneous ground-and-air robotic teams.

Towards evaluating the impact of swarm robotic control strategy on operators’ cognitive load

“…Figure 2 shows the experimental overview and illustrates some of the features of the robotic system, including communication between robots, safety considerations, and human-robot communication. All technical aspects of the robotic system are thoroughly explained in the work of St-Onge, et al [24].…”

“…The code for the robot behaviour is available online 2 . Details of the algorithm for the deployment behaviour and the software infrastructure for the general control of the swarm are presented in [24]. Details of the algorithm for the individual versus group control strategies are presented in [23].…”

Hierarchical Control of Smart Particle Swarms

“…Once a shaping target is reached (both angle and distance), the guides wait for all the other guides to reach their respective shape targets using a mechanism called a barrier [38].…”

“…All the state transitions between the 4 high-level states occur only with an agreement with all the guides. We use a barrier [38], a decentralized method which holds the state of the robots in a standby state until all the robots satisfy the conditions for the state transition. We implemented the barrier using virtual stigmergy, which provides a tuple space storage.…”

Swarm Relays: Distributed Self-Healing Ground-and-Air Connectivity Chains

“…Ground robots, heterogeneous team and flying robots on an average took 100s, 50s and 40s respectively to reach the targets (as discussed in the supplementary material). Finally, we ported the algorithm to our ROS based infrastructure [37] for an outdoor test on a group of 4 larger quadcopters. The outdoor robots used GPS and communicated through an Xbee mesh network.…”