All Outputs (5)

Qualitative Review of Object Recognition Techniques for Tabletop Manipulation (2017)
Conference Proceeding
Wallbridge, C. D., Lemaignan, S., & Belpaeme, T. (2017). Qualitative Review of Object Recognition Techniques for Tabletop Manipulation. In ACM Human-Agent Interaction Conference. , (359-363). https://doi.org/10.1145/3125739.3132593

© 2017 ACM. This paper provides a qualitative review of different object recognition techniques relevant for near-proximity Human- Robot Interaction. These techniques are divided into three categories: 2D correspondence, 3D correspondence and nonvisi... Read More about Qualitative Review of Object Recognition Techniques for Tabletop Manipulation.

Leveraging human inputs in interactive machine learning for human robot interaction (2017)
Conference Proceeding
Senft, E., Lemaignan, S., Baxter, P. E., & Belpaeme, T. (2017). Leveraging human inputs in interactive machine learning for human robot interaction. In Proceedings of the 2017 ACM/IEEE Human-Robot Interaction Conference. , (281-282). https://doi.org/10.1145/3029798.3038385

A key challenge of HRI is allowing robots to be adaptable, especially as robots are expected to penetrate society at large and to interact in unexpected environments with non-technical users. One way of providing this adaptability is to use Interacti... Read More about Leveraging human inputs in interactive machine learning for human robot interaction.

Supervised Autonomy for Online Learning in Human-Robot Interaction (2017)
Journal Article
Senft, E., Baxter, P., Kennedy, J., Lemaignan, S., & Belpaeme, T. (2017). Supervised Autonomy for Online Learning in Human-Robot Interaction. Pattern Recognition Letters, 99, 77-86. https://doi.org/10.1016/j.patrec.2017.03.015

© 2017 When a robot is learning it needs to explore its environment and how its environment responds on its actions. When the environment is large and there are a large number of possible actions the robot can take, this exploration phase can take pr... Read More about Supervised Autonomy for Online Learning in Human-Robot Interaction.

Cellulo: Versatile Handheld Robots for Education (2017)
Conference Proceeding
Ozgür, A., Lemaignan, S., Johal, W., Beltran, M., Briod, M., Pereyre, L., …Dillenbourg, P. (2017). Cellulo: Versatile Handheld Robots for Education. In Proceedings of the 2017 ACM/IEEE Human-Robot Interaction Conference, (119-127). https://doi.org/10.1145/2909824.3020247

© 2017 ACM. In this article, we present Cellulo, a novel robotic platform that investigates the intersection of three ideas for robotics in education: designing the robots to be versatile and generic tools; blending robots into the classroom by desig... Read More about Cellulo: Versatile Handheld Robots for Education.

Child Speech Recognition in Human-Robot Interaction: Evaluations and Recommendations (2017)
Conference Proceeding
Kennedy, J., Lemaignan, S., Montassier, C., Lavalade, P., Irfan, B., Papadopoulos, F., …Belpaeme, T. (2017). Child Speech Recognition in Human-Robot Interaction: Evaluations and Recommendations. In Proceedings of the 2017 ACM/IEEE Human-Robot Interaction Conference. , (82-90). https://doi.org/10.1145/2909824.3020229

© 2017 ACM. An increasing number of human-robot interaction (HRI) studies are now taking place in applied settings with children. These interactions often hinge on verbal interaction to effectively achieve their goals. Great advances have been made i... Read More about Child Speech Recognition in Human-Robot Interaction: Evaluations and Recommendations.