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--- teaching:mfe:ia [2010/03/19 16:58]
mbiro
+++ teaching:mfe:ia [2010/03/19 20:09]
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 The goal of the project is to implement new algorithms for solving this problem on the e-Puck robot and run extensive experiments with this robot in various environments. The project will involve experimentation with about 30 real e-Pucks. The project is tightly connected to the research in swarm robotics carried out at IRIDIA.
+Required skills: The candidates should be acquainted with C/C++ programming and have a working knowledge of the English language.
   * Contacts: [[http://iridia.ulb.ac.be/~mbiro|Mauro Birattari]], Marco Dorigo, Arne Brutschy, Giovanni Pini (IRIDIA)
+===== Studying collaboration between flying robots and ground-based robots =====
+In previous studies, it has been shown that multiple ground-based robots can autonomously form various patterns by attaching to each other. These robots used simple rule sets and local communication to form pre-defined or random patterns. In this thesis, the student will study how flying robots can collaborate with ground-based robots to select and control the pattern formation process. The student will implement the results of his study and various other algorithms that would facilitate such a collaboration. In order to gain a sound understanding of the matter, the student will first study and benchmark collaboration techniques used in existing robotic systems including flying and ground-based robots.
+A possible candidate student must be very motivated, ready to invest extra hours into the thesis, and have a good grasp of C++.  The working  language is English.
+  * Contacts: [[http://iridia.ulb.ac.be/~mbiro|Mauro Birattari]], Marco Dorigo, Nithin Mathews (IRIDIA)
 ===== Adaptive collective alignment with a swarm of e-puck robots =====
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-* Contacts: [[http://iridia.ulb.ac.be/~mbiro|Mauro Birattari]], Marco Dorigo, Eliseo Ferrante, Ali Emre Turgut (IRIDIA)
+  * Contact: [[http://iridia.ulb.ac.be/~mbiro|Mauro Birattari]], Marco Dorigo, Eliseo Ferrante, Ali Emre Turgut (IRIDIA)
+===== Scalable aggregation in swarm robotics without global information or environmental clues =====
+Several studies in biology have shown that group of social insects are able to gather to a particular spot. This process is usually driven by environmental clues such as shadows projected by a shelter (cockroaches) or temperature gradients (bees). These studies have been a source of inspiration for several algorithms in swarm robotics. Is it possible to achieve the same result without an environmental clue? Do we need global information in order to let a group of robot gather in one place?
+The goal of this project is to study how to solve an aggregation task without relying on environmental clues or global signaling. The problem can be seen as an exploration-exploitation trade-off tackled by a single robot. The robot has to select between keeping exploring, that is, finding the the largest aggregate, or exploiting, that is join a previously created aggregate. The study will be conducted only in simulation and will concern comparing different approaches for decision making or different communication strategies.
+Required skills: The candidates should be acquainted with C++ programming and have a working knowledge of the English language.
+  * Contact: [[http://iridia.ulb.ac.be/~mbiro|Mauro Birattari]], Marco Dorigo, Eliseo Ferrante, Ali Emre Turgut (IRIDIA)
+===== A comparison of decision-making strategies for adaptive foraging in swarm robotics =====
+Group of social insects are able to efficiently find the (shortest) path to the a food source and even to differentiate between the quality of two food sources. Studies with ants showed that this mechanism is driven by the perception of stimuli from chemical substances like pheromone. Moreover ants are able to collectively modify their choices if there are changes in the environment, that is, if a source becomes better than another. These ideas have been a source of inspiration for several algorithms in swarm robotics which solves a similar problem (retrieval of objects) by using different types of stimuli such as the encounter rate of objects.
+The goal of this project is to perform a study on how to solve a foraging task in which robots have to choose between staying at the nest or go foraging for different energy sources. The optimal strategy might change over time. What happens if all the robots go to the best source? Will these "traffic jams" slow the process? Is it possible to avoid this problem? What if source quality changes over time? The study will be conducted only in simulation and will concern comparing different approaches and different metrics to measure stimuli.
+Required skills: The candidates should be acquainted with C++ programming and have a working knowledge of the English language.
+  * Contact: [[http://iridia.ulb.ac.be/~mbiro|Mauro Birattari]], Marco Dorigo, Eliseo Ferrante, Manuele Brambilla (IRIDIA)
 ===== Kaleidoscope: Creating temporal motion patterns in a swarm of robots =====