KlaskTron: An Open-Source Platform for Physical Adversarial Multi-Agent RL
Overview
This paper introduces KlaskTron, an open-source, low-cost (<$2500 USD) desktop-scale robotic testbed for adversarial multi-agent reinforcement learning (MARL). The platform is based on the dynamic tabletop game KLASK and features dual CoreXY gantries with high-torque brushless motors. It includes a complete ecosystem comprising hardware designs (CAD, BOM), a GPU-native digital twin in NVIDIA Isaac Lab for high-fidelity simulation, and a validated sim-to-real baseline using a learned neural actuator model that enables zero-shot policy transfer. All project assets, including assembly documentation, inference software, and MARL setup, are released publicly to ensure reproducibility.
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Reported quantity · cost: 2500 other · Basis not reported
“ey barrier is infrastructural: physical platforms are often prohibitively expensive, require specialized facilities, or lack open mechanisms and designs for reproducibility. We introduce KlaskTron, an open-source, low-cost (<\$2500 USD), desktop-scale robotic testbed for adversarial MARL based on the dynamic tabletop game KLASK. The platform features dual CoreXY gantries with high-torque brushless motors, enabling th”
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- arXiv Robotics — research abstractsSignalKlaskTron: An Open-Source Platform for Physical Adversarial Multi-Agent RL
This paper introduces KlaskTron, an open-source, low-cost (<$2500 USD) desktop-scale robotic testbed for adversarial multi-agent reinforcement learning (MARL). The platform is based on the dynamic tabletop game KLASK and features dual CoreXY gantries with high-torque brushless motors. It includes a complete ecosystem comprising hardware designs (CAD, BOM), a GPU-native digital twin in NVIDIA Isaac Lab for high-fidelity simulation, and a validated sim-to-real baseline using a learned neural actuator model that enables zero-shot policy transfer. All project assets, including assembly documentation, inference software, and MARL setup, are released publicly to ensure reproducibility.
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