Abstract
The act of assisted feeding is a challenging task that requires a good reactive planning strategy to cope with an unpredictable environment. It can be seen as a tracking task, where some end effector must travel to a moving goal. This work builds upon state of the art algorithms, such as Discriminative Optimization, making use of a Kinect camera and a modular robotic arm to implement a closed form system that performs assisted feeding. It presents two different approaches: the use of a variable rate function for updating the trajectory with information on the moving goal, and the definition of different risk regions that will shape a safer trajectory.
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References
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Acknowledgements
This work benefited greatly from professor Howie Choset’s support, who provided access to the Hebi Modules used in this work. We also thank our colleagues from the biorobotics lab at CMU who provided valuable insights and expertise on these modules. This research was supported in part by Fundação para a Ciencia e a Tecnologia [UID/EEA/50009/2013]. Manuel Marques is partially supported by FCT project [IF/00879/2012].
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Silva, C., Vongkulbhisal, J., Marques, M., Costeira, J.P., Veloso, M. (2017). Feedbot - A Robotic Arm for Autonomous Assisted Feeding. In: Oliveira, E., Gama, J., Vale, Z., Lopes Cardoso, H. (eds) Progress in Artificial Intelligence. EPIA 2017. Lecture Notes in Computer Science(), vol 10423. Springer, Cham. https://doi.org/10.1007/978-3-319-65340-2_40
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DOI: https://doi.org/10.1007/978-3-319-65340-2_40
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