@article{57224,
  author       = {{Mujahed, Muhannad and Fischer, Dirk and Mertsching, Bärbel}},
  issn         = {{0921-8890}},
  journal      = {{Robotics and Autonomous Systems}},
  pages        = {{93--110}},
  publisher    = {{Elsevier BV}},
  title        = {{{Admissible gap navigation: A new collision avoidance approach}}},
  doi          = {{10.1016/j.robot.2018.02.008}},
  volume       = {{103}},
  year         = {{2018}},
}

@article{57226,
  author       = {{Mujahed, Muhannad and Fischer, Dirk and Mertsching, Bärbel}},
  issn         = {{0921-8890}},
  journal      = {{Robotics and Autonomous Systems}},
  pages        = {{15--30}},
  publisher    = {{Elsevier BV}},
  title        = {{{Tangential Gap Flow (TGF) navigation: A new reactive obstacle avoidance approach for highly cluttered environments}}},
  doi          = {{10.1016/j.robot.2016.07.001}},
  volume       = {{84}},
  year         = {{2016}},
}

@article{20255,
  abstract     = {{By compiling macroscopic models we analyze the adaptive behavior in a swarm of autonomous robots generated by a bio-inspired, distributed control algorithm. We developed two macroscopic models by taking two different perspectives: A Stock & Flow model, which is simple to implement and fast to simulate, and a spatially resolved model based on diffusion processes. These two models were compared concerning their prediction quality and their analytical power: One model allowed easy identification of the major feedback loops governing the swarm behavior. The other model allowed analysis of the expected shapes and positions of observable robot clusters. We found a high correlation in the challenges posed by both modeling techniques and we highlighted the inherent problems of inferring emergent macroscopic rules from a microscopic description of swarm behavior.}},
  author       = {{Schmickl, Thomas and Hamann, Heiko and Wörn, Heinz and Crailsheim, Karl}},
  issn         = {{0921-8890}},
  journal      = {{Robotics and Autonomous Systems}},
  number       = {{9}},
  pages        = {{913--921}},
  title        = {{{Two different approaches to a macroscopic model of a bio-inspired robotic swarm}}},
  doi          = {{10.1016/j.robot.2009.06.002}},
  volume       = {{6}},
  year         = {{2009}},
}