'guten-learn-radio-image', 'class' => 'Guten_Learn_Customize_Control_Radio_Image', 'sanitize' => array( 'Guten_Learn_Customizer', 'sanitize_number' ), )); {"id":330,"date":"2023-04-05T14:00:00","date_gmt":"2023-04-05T11:00:00","guid":{"rendered":"https:\/\/aspida.ee.duth.gr\/?p=330"},"modified":"2023-04-13T14:22:08","modified_gmt":"2023-04-13T11:22:08","slug":"an-rl-robotic-arm-approach-with-a-spiking-actor","status":"publish","type":"post","link":"https:\/\/aspida.ee.duth.gr\/en\/an-rl-robotic-arm-approach-with-a-spiking-actor\/","title":{"rendered":"An RL robotic arm approach with a spiking actor"},"content":{"rendered":"
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If you are interested in the future of robotics and assistive technology, check out the following video and see our proposed approach in action!<\/p><\/blockquote><\/figure>\n\n\n\n

Are you curious to see how a hybrid variation of the deep deterministic policy gradient (DDPG) reinforcement learning approach can reduce energy consumption while improving the performance of a 6 degree of freedom robotic arm in the target-reach task? Our recent publication<\/a> proposed this approach, which employs a spiking neural network (SNN) for the actor model and a DNN for the critic one, and uses a combination of RGB and laser scan data for collision avoidance and object detection.<\/p>\n\n\n\n

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