Context-Specific Intention Awareness through Web Query ICRA 2015 – NO.137 Nominated as best conference paper award, best student paper award, best cognitive robotics paper award. Context-Specific Intention Awareness through Web Query Rui Liu Dr. Xiaoli Zhang Jeremy Webb Songpo Li Colorado School of Mines, Colorado, USA Intelligent Healthcare Robotics Lab bio, cooperation

Colorado School of Mines, Colorado, USA Introduction Context-Specific Intention Awareness Explores environmental context to infer intention in robotic caregiving Implicitly infer human intention without much user involvements Challenges Limited knowledge of Intention-environment correlation: source, cost Lack knowledge learning in new situations Solution: WebIA Collect knowledge by web query Update knowledge by situations Colorado School of Mines, Colorado, USA Intelligent Healthcare Robotics Lab definition, important, challenging, to solve it.

Colorado School of Mines, Colorado, USA WebIA Framework Performance unsatisfied >> Learn >>Update Colorado School of Mines, Colorado, USA Intelligent Healthcare Robotics Lab flow, update

Colorado School of Mines, Colorado, USA WebIA Answering 2 questions: Is WebIA feasible ? If feasible, how good it is ? Colorado School of Mines, Colorado, USA Intelligent Healthcare Robotics Lab short mention 2 questions.

Colorado School of Mines, Colorado, USA Evaluation Knowledge Acquisition Web query 1470 wikihow webpages Survey 120 volunteers Robot-involved E xperiments (a) Trained situation (b) Untrained new situation Colorado School of Mines, Colorado, USA Intelligent Healthcare Robotics Lab 1. short introduction.

Colorado School of Mines, Colorado, USA Evaluation Cup-related Commonsense Knowledge from the Web IA performance Drink: 100% Wash: 85% Consistency Comparison of Knowledge from Web & Survey Specific context is important for specific intention Consistent New Situation Before Learning: 57.5% After Learning: 100% Colorado School of Mines, Colorado, USA Intelligent Healthcare Robotics Lab

Colorado School of Mines, Colorado, USA Conclusion WebIA effectively learned the knowledge of human-environment relation and accurately inferred human intention in specific situations. Feasible: WebIA has the potential to query vast and valuable knowledge from the internet to assist human-robot interaction Reasonable: Web knowledge is helpful in filling robots’ knowledge gap for new situation adaptation Economic: WebIA reduces the training cost Colorado School of Mines, Colorado, USA Intelligent Healthcare Robotics Lab effectively learn, accurately infer.

Colorado School of Mines, USA Authors Rui Liu, PhD Student Interests: robot knowledge, computational linguistics and machine learning Research Gate: https://goo.gl/UUASbB Google Scholar: https://goo.gl/CpgXNV Xiaoli Zhang, Assistant Professor Interests: intelligent human-robot interaction, human intention awareness, robotics system design and control, haptics, and their applications in healthcare fields Colorado School of Mines, USA Intelligent Healthcare Robotics Lab