self-organizing systems; swarm intelligence; heterogeneous agents; search-and-rescue; wireless multi-hop networking; flying robots; swarms of heterogeneous agents; humans; animals; micro-air-vehicles; synergistic interaction and control
M. Asadpour, M. Burger, F. Schuiki, K.A. Hummel (2015),
Needle in a Haystack: On Limiting the Search Effort in Mission-aware Packet Forwarding for Drones, ACM, Paris.
Flushing Eduardo Feo, Gambardella Luca, Di Caro Gianni (2014), A mathematical programming approach to collaborative missions with heterogeneous teams, in
27th IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE, IEEE.
Gergely Anna, Doka A., Topal J., Miklosi Adam (2014), Dogs (Canis familiaris) are able to generalize directional acoustic signals to different contexts and tasks, in
Applied Animal Behaviour Science, 156, 54-61.
Asadpour Mahdi, Van den Bergh Bertold, Giustiniano Domenico, Hummel Karin Anna, Pollin Sofie, Plattner Bernhard (2014), Micro aerial vehicle networks: an experimental analysis of challenges and opportunities, in
IEEE Communications Magazine, 52(7), 141-149.
Gerencser Linda, Vasarhelyi Gabor (2014), On dogs and widgets - the automatization of behaviour observation, in
Magyar Tudomany, 176, 28-35.
{Feo-Flushing} E., Kudelski M., Nagi J., Gambardella L., {Di Caro} G. A. (2014), Poster Abstract: Link Quality Estimation -- A Case Study for On-line Supervised Learning in Wireless Sensor Networks, in
5th Workshop on Real- World Wireless Sensor Networks (REALWSN), Springer, Springer.
Gergely Anna, Miklosi Adam (2014), Robot-animal interactions as a new research tool, in
Magyar Todomany, 176, 44-50.
Asadpour Mahdi, Egli Simon, Hummel Karin Anna, Giustiniano Domenico (2014), Routing in a fleet of micro aerial vehicles: First experimental insights, in
Third ACM Workshop on Airborne Networks and Communications, ACM, ACM.
Flushing Eduardo Feo, Kudelski M., Gambardella Luca, Di Caro Gianni A. (2014), Spatial prediction of wireless links and its application to the path control of mobile robots, in
9th IEEE International Symposium on Industrial Embedded Systems (SIES), IEEE, IEEE.
Di Caro Gianni A. (2014), Use of time-dependent spatial maps of communication quality for networkaware multi-robot path planning, in
8th International Workshop on Wireless Sensor, Actuator and Robot Networks (WiSARN), Springer, Springer.
Feo Eduardo, Di Caro Gianni (2013), A Flow-based Optimization Model for Throughput-oriented Relay Node Placement in Wireless Sensor Networks, in
28th ACM Symposium on Applied Computing, Coimbra, PortugalACM, ACM.
Asadpour M., Giustiniano D., Hummel K.A., Heimlicher S. (2013), Characterizing 802.11n Aerial Communication, in
Airborne, Mobihoc WS 2013, ACM, ACM.
{Feo Flushing} E., Kudelski M., Gambardella L., {Di Caro} G. A. (2013), Connectivity-aware planning of search and rescue missions, in
11th IEEE Intl. Symposium on Safety, Security, and Rescue Robotics (SSRR), IEEE, IEEE.
Asadpour M., Giustiniano D., Hummel K.A. (2013), From Ground to Aerial Communication: Dissecting WLAN 802.11n for the Drones, in
ACM Wintech 2013, ACM, ACM.
Gerencsér L., Vasarhelyi G., Nagy M., Miklósi Á. (2013), Identification of Behaviour in Freely Moving Dogs (Canis familiaris) Using Inertial Sensors, in
PLOSOne, 8.10(e77814), 77814.
Asadpour M., Giustiniano D., Hummel K.A., Heimlicher S., Egli S. (2013), Now or Later?: Delaying Data Transfer in Time-critical Aerial Communication, in
ACM CONEXT 2013, ACM, ACM.
{Di Caro} G. A., Kudelski M., {Feo Flushing} E., Nagi J., Ahmed I., Gambardella L. (2013), On-line supervised learning of link quality estimates in wireless networks, in
12th IEEE/IFIP Annual Mediterranean Ad Hoc Networking Workshop (Med-Hoc-Net), IEEE, IEEE.
{Feo Flushing} E., Gambardella L., {Di Caro} G. A. (2013), Strategic control of proximity relationships in heterogeneous search and rescue teams, in
3rd IROS Workshop on Robots and Sensors integration in future rescue INformation system (ROSIN), IEEE, IEEE.
Asadpour M., Giustiniano D., Hummel K.A., Egli S. (2013), UAV Networks in Rescue Missions, in
ACM Wintech 2013, ACM, ACM.
Gergely A., Petro E., Topal J., Miklósi Á. (2013), What are you or who are you? The emergence of social interaction between dog and an Unidentified Moving Object (UMO), in
PLOSOne, 8.8(e72727), 72727.
Feo Eduardo, Gambardella Luca, Di Caro Gianni (2012), GIS-based Mission Support System for Wilderness Search and Rescue with Heterogeneous Agents, in
2nd IROS Workshop on Robots and Sensors integration in future rescue INformation, Vilamoura, PortugalIEEE, IEEE.
Gerencser Linda, Miklosi Adam (2012), Potential Application of Behaviourally Enriched Robots in the Study of Animal Behaviour, in
3rd IEEE International Conference on Cognitive Infocommunications, IEEE, IEEE.
Feo Eduardo, Di Caro Gianni (2011), Optimal Relay Node Placement for Throughput Enhancement in Wireless Sensor Networks, in
50th FITCE International Congress -- ICT: brigding an ever shifting digital divide, IEEE, IEEE.
Hauert S., Leven S., Varga M., Ruini F., Cangelosi A., Zufferey J.-C., Floreano D. (2011), Reynolds Flocking in Reality with Fixed-wing Robots: Communication Range vs. Maximum Turning Rate, in
Intelligent Robots and Systems (IROS), 2011 IEEE/RSJ , San Francisco, USAIEEE, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
Feo Flushing E., Nagi J., Di Caro G.A., A Mobility-assisted Protocol for Supervised Learning of Link Quality Estimates in Wireless Networks, in
International Conference on Computing, Networking and Communications (ICNC), M^3, IEEE, International Conference on Computing, Networking and Communications (ICNC) 2012.
Andre T., Hummel K.A., Schoellig A., Yanmaz E., Asadpour M., Bettstetter C., Grippa P., Hellwagner H., Sand S., Zhang S., Application-Driven Design of Aerial Communication Networks, in
IEEE Communication Magazine, Special Issue on Enabling Next Generation Airborne Communications (to a.
Feo Eduardo, Di Caro Gianni, Exploiting Synergies between Exact and Heuristic Methods in Optimization: an application to the Relay Placement Problem in Wireless Sensor Networks, in
7th International Conference on Bio-Inspired Models of Network, Information, and Computing Systems , Lugano, SwitzerlandSpringer, Springer.
Feo Eduardo, Di Caro Gianni, Relay Node Placement for Performance Enhancement with Uncertain Demand: a Robust Optimization Approach, in
11th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless , IEEE, IEEE.
M. Asadpour, K.A. Hummel, D. Giustiniano, S. Draskovic, Route or Carry: Motion-driven Packet Forwarding in Micro Aerial Vehicle Networks, in
IEEE Transactions on Mobile Computing, 1.
The proposed research is about laying the foundations for the design, implementation, and adaptive control of heterogenous multi-agent systems that are composed of humans, animals, and robots working in cooperation to solve distributed tasks that require a wide diversity of sensory-motor and cognitive skills. In the following, we will refer to such systems as mixed swarms, hence the project code name SWARMIX. The aim is to provide each component of the mixed swarm with a high level of autonomy in order to allow it to fully exploit its own unique skills and abilities, and at the same time to set up close bidirectional interactions and information flows between all system components in order to ensure overall synergistic cooperation. The main novelty ofthis project lies in the cooperative integration of a possibly large number of humans, animals, and robots in tight cooperation in one single networked system with distributed control. To the best of our knowledge this would be the first research addressing peer-to-peer cooperation between humans, animals, and robots.The research work in the SWARMIX project will be guided by the creation of a specific validation scenario composed of humans, dogs, and small-sized UAVs aimed at performing search-and-rescue (SAR) missions in outdoor civilian domains. We believe that concentrating on one example is important given the vast possibilities in the ways mixed swarms can be composed and applied. A practical implementation will help guide the development of theoretical work and provide a testbed for new ideas. The choice for search-and-rescue missions is inspired by their practical/humanitarian relevance, and by the fact that these applications are often used in the scientific domain as referencetest to assess the performance of collective cooperative systems. In order to validate our research and to emphasize the synergistic cooperation between partners, the SWARMIX project will include a rigorous experimental protocol in the context of the SAR scenario, where success will be measured by the capability of the swarm as aunit to locate targets in distributed environments more reliably and/or faster than each group of agents in isolation or even in pairwise combinations.Our research will focus on the one hand on the identification and development of technology that is needed to use and extend the sensory-motor skills of the different agents and to support communication between them, and on the other hand on the creation of intelligent algorithms and protocols that allow synergistic interaction and control within the heterogenous swarm. To break down the complexity of the generalproblem at hand, we identify four fundamental directions of research, that are addressed in the individual sub-projects: 1) wireless networking for highly dynamic heterogenous agents studied at ETHZ-TIK, 2) adaptive profiling of agent and mission status, and swarm-level planning of agent activities studied at IDSIA, 3) intuitive inter-agent communication interfaces and local control of agent behaviors studied at EPFL-LIS, 4) training, control, and monitoring of dogs for full integration in the swarm studied at ELU. Each of these four research directions stands by itself and addresses fundamental scientific issues. It is from the interaction among these four research directions and their integration into one common view and real-life application that we can obtain a true synergy of results and provide answers to the main challenge of this project, namely adaptive cooperation in heterogenous, multi-agent systems to perform tasks more efficiently.