Balancing real or simulation cart-pole system with RL

Equipment: Cart-pole simulator and real cart-pole used by Tobi Delbruck for MPC tests


Possible directions:

  • Online Spiking RL (R-Eprop) for non-ideal cartpole stabilization solving in simulation after transfer learning of weights for ideal cartpole trained with DQN 

  • Deep Q-Learning for cartpole swing-up in simulation

  • Implementation of inference DQN on real cartpole

  • Possible simulation of cartpole with event-based tracked input instead of positions + velocities


Possible Challenges:

  • Use an event-based tracking algorithm to compute the shape coordinates over time

  • Define the RL policy (e.g., actions, state, reward) in simulation based on an event-camera output

  • Transfer the policy to the real cart-pole

  • Learn how to control the cart-pole

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Day Time Location
Tue, 02.05.2023 22:00 - 23:00 Lobby
Wed, 03.05.2023 16:00 - 17:00 Disco


Shreyan Banerjee
Maxime Fabre
Luna Gava