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Assistance networks for dynamic multirobot tasks

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Abstract

In this paper, we consider dynamic multirobot tasks that can be done by any of the robots, but only with the assistance of any other robot. We propose a novel approach based on the concept of ‘assistance networks’ with two complementary aspects, namely assistant finding and network topology update. Each robot, encountering a new task, seeks an assisting robot among its immediate neighbors in the assistance network in a decentralized manner. The network topology is defined based on pairwise stability via payoff functions that consider general task-related guidelines. As such, the number of potential assisting robots can be ensured a priori depending on tasks’ requirements. As robots move around, the topology is updated via pairwise games. If the games are conducted by a network coordinator, each game is shown to result in a pairwise stable network. A series of simulation and experimental results in a variety of different scenarios demonstrate that the robots are able to get assistance or give assistance flexibly.

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Notes

  1. While we consider tasks that can be completed with assistance from one robot, our approach can be extended to multi-robot assistance problems.

  2. For the interested reader, the detailed algorithm of task automaton is given in Appendix 2.

  3. For notational brevity, the time argument will be omitted whenever it is clear from the context.

  4. Although not investigated in this paper, the unit cost c may become varying for each robot.

  5. The details of the experimental setup are described in Appendix 1.

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Acknowledgments

This work has been supported in part by Bogazici University (BAP 5169 and BAP 7222) and by TUBITAK (111E285).

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Authors and Affiliations

  1. Intelligent Systems Laboratory, Electrical and Electronics Engineering Department, Bogazici University, Bebek, 34342, Istanbul, Turkey

    Haluk Bayram & H. Iṣıl Bozma

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  1. Haluk Bayram
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Correspondence to Haluk Bayram.

Appendices

Appendix 1: Experimental setup

All the robots are equipped with on-board processing, gyro, and Hokuyo laser range scanner with 4m field of depth and encoders. They move with maximum speed around 0.1 meters/second in the workspace. The robots have been programmed using Robot Operating System (ROS). The map of workspace is built using gmapping package in ROS with one of the robots prior to the experiment and is shared by all the robots. Localization is achieved via using the AMCL package that is available in ROS. The control software has a special novel architecture based on sense-communicate-act paradigm with communication and network update modules (Karaoguz et al. 2013). The communication module enables the robots to communicate with potential assisting robots as deemed by the current assistance network, while the network update module has different functionalities depending on the running robot. All robots other than the network coordinator simply relay their position information to the coordinator and wait for the updated network topology. The network coordinator receives each robot’s information and updates the network topology and informs all the robots accordingly. For patrolling, a modified version of feedback-based navigation is used (Karagöz et al. 2014). For this, MPFR library is used to operate on the big numbers while implementing the navigation controller (Fousse et al. 2007). All the robots also have a task detection module that is responsible for detecting encountered tasks.

Appendix 2: Algorithm for robot’s task automaton

The task automaton in Fig. 1 is defined by Algorithm 1.

figure c

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Bayram, H., Bozma, H.I. Assistance networks for dynamic multirobot tasks. Auton Robot 40, 615–630 (2016). https://doi.org/10.1007/s10514-015-9484-6

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