Pera-Swarm explores the powerful combination of Swarm Robotics and Mixed Reality (MR) to create a seamless integration between the real and virtual worlds. The project demonstrates how physical robots can interact with virtual environments in real time, paving the way for applications that merge simulation with tangible operations.
Swarm Robotics, inspired by the collective intelligence of nature, focuses on how multiple robots can coordinate as a system to perform complex tasks efficiently. When enhanced with Mixed Reality, these robot swarms are not only visible in their physical form but can also be extended, manipulated, and observed in immersive digital spaces.
Another research work by Pera-Swarm, "Simultaneous Localization and Mapping with Cost Effective Sensors" was presented at the 2025 International Research Conference on Smart C...
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The Department of Computer Engineering, University of Peradeniya, is proud to present Pera-Swarm, an innovative research project, at EngEx 2025, the grand exhibition cele...
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Mixed-Reality based Swarm Robot Simulation Framework is one of the main outcomes of the Pera-Swarm project, and the first paper publication under the project is now published ...
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We conducted an “Introduction Session” for enthusiastic students of the Faculty of Engineering, University of Peradeniya, on Swarm Robotics and show...
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The study delves into the realm of swarm robotics, where agents collaborate to efficiently explore and map unknown environments...
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Pera Swarm's Swarm Capable and Reconfigurable Agent is its first modular robot system, designed to...
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A high-level programming and compiler framework for Swarm Robotics
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An open-source Mixed-Reality Simulator and a Visualizer to simulate Swarm Intelligence behaviors
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Obstacle bots for the existing swarm research project of the Department of Computer Engineering, University of Peradeniya. These robots can create a challenging patterns using movements in a self-created potential surface with collision-avoiding.
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General purpose swarm robots with a GUI to monitor and control them remotely
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Pair-behaviors, neighbor-cluster behaviors for aggregation and pattern formation global behaviors
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Application of swarm intelligence with general purpose robots
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