Self-Organized Collective Decision-Making in a 100-Robot Swarm
Authors: Gabriele Valentini, Heiko Hamann, Marco Dorigo
AAAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We study the effectiveness and robustness of the proposed strategy using a swarm of 100 Kilobots and we focus on the impact of the neighborhood size over the dynamics of the system. |
| Researcher Affiliation | Academia | Gabriele Valentini IRIDIA, Universit e Libre de Bruxelles 50 Av. F. Roosevelt, Brussels, Belgium +32 2 650 2712, gvalenti@ulb.ac.be, http://iridia.ulb.ac.be/ gvalentini/ Heiko Hamann Department of Computer Science University of Paderborn Paderborn, Germany heiko.hamann@uni-paderborn.de Marco Dorigo IRIDIA Universit e Libre de Bruxelles Brussels, Belgium mdorigo@ulb.ac.be |
| Pseudocode | No | The paper describes the robot's control algorithm as a "finite-state machine of 4 states (Fig. 1a)", and describes its steps in text, but it does not provide formal pseudocode or an algorithm block. |
| Open Source Code | No | The paper does not contain any statement about releasing source code or provide a link to a code repository. |
| Open Datasets | No | The paper describes a custom experimental setup with 100 Kilobots in a rectangular arena where sites A and B are emulated with infrared beacons. This is an custom experimental environment, not a publicly available dataset with concrete access information. |
| Dataset Splits | No | The paper does not specify explicit training, validation, or test dataset splits. It describes experimental runs (10 runs of 90 min) and collects data dynamically from the robot swarm. |
| Hardware Specification | Yes | The Kilobot is a low-cost, 3.3 cm robot with stick-slip motion (1 cm/s forward, π/4 rad/s turn in place), one ambient light sensor, and infrared communication capabilities (3-byte messages in a range up to 10-20 cm). We place N = 100 robots in a rectangular arena of 100 x 190 cm2 (Fig. 1b). |
| Software Dependencies | No | The paper describes the distributed algorithm and the robot's finite-state machine logic, but it does not list any specific software dependencies with version numbers (e.g., programming languages, libraries, operating systems, or specific simulation software). |
| Experiment Setup | Yes | We place N = 100 robots in a rectangular arena of 100 x 190 cm2 (Fig. 1b). We consider a scenario where site A is twice as good compared to site B (ρA = 1 and ρB = 0.5). We perform two series of experiments (10 runs of 90 min for each series) where we vary the maximum number Nmax of opinion messages that a robot is allowed to receive before applying the majority rule. For convenience, we refer to the maximum size Gmax = Nmax + 1 of the group of opinions used in the majority rule which includes the robot current opinion (Gmax {5, 25}). |