Explanation Generation for Autonomous Robot Decision-Making
2024年1月1日
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1 min read
We build frameworks that let autonomous robots explain their decision-making processes and the underlying reasoning to people in an understandable way. Through distributed representations of world models, we visualize the robot’s internal states and its estimates of others’ world models, supporting reliable human-robot collaboration.
Related papers:
- Site Hu, Takato Horii, Takayuki Nagai. “Adaptive and Transparent Decision-Making in Autonomous Robots through Graph-Structured World Models”. Advanced Robotics, 38(22), 1579-1599, 2024.
- Tatsuya Sakai, Kazuki Miyazawa, Takato Horii, Takayuki Nagai. “A Framework of Explanation Generation toward Reliable Autonomous Robots”. Advanced Robotics, 35(17), 1054-1067, 2021.
- Tatsuya Sakai, Takato Horii, Takayuki Nagai. “Acquisition of Distributed Representations of World Models Using Graph2vec and Estimation of Others’ World Models” (in Japanese). Journal of the Robotics Society of Japan, 40(2), 166-169, 2022.
Authors
Takato Horii
(he/him)
Associate Professor
Associate Professor at Graduate School of Engineering Science, Osaka University.
Research interests include cognitive developmental robotics, computational modeling
of emotional development, and human-robot interaction.