One-shot assistance estimation from expert demonstrations for a shared control wheelchair system

Kucukyilmaz, Ayse and Demiris, Yiannis (2015) One-shot assistance estimation from expert demonstrations for a shared control wheelchair system. In: 24th IEEE International Symposium on Robot and Human Interactive Communication 2015 (RO-MAN'15), 31 August - 4 September 2015, Kobe, Japan.

Full content URL:

Kucukyilmaz-OneShot-RoMan15.pdf - Whole Document

Item Type:Conference or Workshop contribution (Paper)
Item Status:Live Archive


An emerging research problem in the field of assistive robotics is the design of methodologies that allow robots to provide human-like assistance to the users. Especially within the rehabilitation domain, a grand challenge is to program a robot to mimic the operation of an occupational therapist, intervening with the user when necessary so as to improve the therapeutic power of the assistive robotic system. We propose a method to estimate assistance policies from expert demonstrations to present human-like intervention during navigation in a powered wheelchair setup. For this purpose, we constructed a setting, where a human offers assistance to the user over a haptic shared control system. The robot learns from human assistance demonstrations while the user is actively driving the wheelchair in an unconstrained environment. We train a Gaussian process regression model to learn assistance commands given past and current actions of the user and the state of the environment. The results indicate that the model can estimate human assistance after only a single demonstration, i.e. in one-shot, so that the robot can help the user by selecting the appropriate assistance in a human-like fashion.

Keywords:assistive robotics, assisted mobility, Gaussian Processes, learning by demonstration
Subjects:H Engineering > H671 Robotics
G Mathematical and Computer Sciences > G760 Machine Learning
Divisions:College of Science > School of Computer Science
Related URLs:
ID Code:29367
Deposited On:17 Nov 2017 11:57

Repository Staff Only: item control page