Trajectory Planning of Robotic Manipulator in Dynamic Environment Exploiting DRL
<|reference_start|>Trajectory Planning of Robotic Manipulator in Dynamic Environment Exploiting DRL: This study is about the implementation of a reinforcement learning algorithm in the trajectory planning of manipulators. We have a 7-DOF robotic arm to pick and place the randomly placed block at a random target point in an unknown environment. The obstacle is randomly moving which creates a hurdle in picking the object. The objective of the robot is to avoid the obstacle and pick the block with constraints to a fixed timestamp. In this literature, we have applied a deep deterministic policy gradient (DDPG) algorithm and compared the model's efficiency with dense and sparse rewards.<|reference_end|>
@article{ahmad2024trajectory,
    title={Trajectory Planning of Robotic Manipulator in Dynamic Environment
  Exploiting DRL},
    author={Osama Ahmad, Zawar Hussain, Hammad Naeem},
    journal={arXiv preprint arXiv:2403.16652},
    year={2024},
    archivePrefix={arXiv},
    eprint={2403.16652},
    primaryClass={cs.RO cs.SY eess.SY}
}