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Soft Actor-Critic for Navigation of Mobile Robots

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Abstract

This paper provides a study of two deep reinforcement learning techniques for application in navigation of mobile robots, one of the techniques is the Soft Actor Critic (SAC) that is compared with the Deep Deterministic Policy Gradients (DDPG) algorithm in the same situation. In order to make a robot to arrive at a target in an environment, both networks have 10 laser range findings, the previous linear and angular velocity, and relative position and angle of the mobile robot to the target are used as the network inputs. As outputs, the networks have the linear and angular velocity of the mobile robot. The reward function created was designed in a way to only give a positive reward to the agent when it gets to the target and a negative reward when colliding with any object. The proposed architecture was applied successfully in two simulated environments, and a comparison between the two referred techniques was made using the results obtained as a basis and it was demonstrated that the SAC algorithm has a superior performance for the navigation of mobile robots than the DDPG algorithm (Code available at https://github.com/dranaju/project).

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Materials Availability

Available in GitHub https://github.com/dranaju/project.

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Acknowledgements

We would like to thank Fabio Ugalde Pereira, by sharing the idea and environments with symmetric and assymmetric map formats, and all participants of VersusAI, by interchanging ideas and thoughts in the area of Robotics and Artificial Intelligence.

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Authors and Affiliations

  1. Federal University of Rio Grande, Rio Grande, RS, Brazil

    Junior Costa de Jesus & Ricardo Bedin Grando

  2. Federal University of Santa Maria, Santa Maria, RS, Brazil

    Victor Augusto Kich & Alisson Henrique Kolling

  3. Federal Institute of Espirito Santo, Serra, ES, Brazil

    Marco Antonio de Souza Leite Cuadros

  4. Department of Processing of Electrical Energy (DPEE), Federal University of Santa Maria, Santa Maria, RS, Brazil

    Daniel Fernando Tello Gamarra

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  1. Junior Costa de Jesus
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  2. Victor Augusto Kich
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  6. Daniel Fernando Tello Gamarra
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Contributions

- Junior Costa de Jesus conceived the research, writing of the article, designed and program the experiments, collected and processed the test data.

- Ricardo Bedin Grando write the article, collected and processed the test data.

- Victor Augusto Kich write the article, program the experiments, collected and processed the test data.

- Alisson Henrique Kolling write the article, program the experiments, collected and processed the test data.

- Marco Antonio de Souza Leite Cuadros discussion and conception of the main ideas of the article, provided valuable comments.

- Daniel Fernando Tello Gamarra conceived the research, writing of the article and discussion of the main ideas of the article.

Corresponding author

Correspondence to Junior Costa de Jesus.

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de Jesus, J., Kich, V.A., Kolling, A.H. et al. Soft Actor-Critic for Navigation of Mobile Robots. J Intell Robot Syst 102, 31 (2021). https://doi.org/10.1007/s10846-021-01367-5

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