Investigated reinforcement learning (RL) algorithms using the Franka Emika Panda arm in PyBullet, achieving 100% success in reaching tasks. SAC improved pushing performance to 95%, while DDPG led in pick-and-place tasks. On-policy methods like PPO and A2C showed limited effectiveness.
☆12Jan 6, 2025Updated last year
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