Richard G. Freedman

Learn More
We examine new ways to perform plan recognition (PR) using natural language processing (NLP) techniques. PR often focuses on the structural relationships between consecutive observations and ordered activities that comprise plans. However , NLP commonly treats text as a bag-of-words, omitting such structural relationships and using topic models to break(More)
The use of robots in stroke rehabilitation has become a popular trend in rehabilitation robotics. However, despite the acknowledged value of customized service for individual patients, research on programming adaptive therapy for individual patients has received little attention. The goal of the current study is to model teletherapy sessions in the form of(More)
The ability to identify what humans are doing in the environment is a crucial element of responsive behavior in human-robot interaction. We examine new ways to perform plan recognition (PR) using natural language processing (NLP) techniques. PR often focuses on the structural relationships between consecutive observations and ordered activities that(More)
We consider ways to improve the performance of unsuper-vised plan and activity recognition techniques by considering temporal and object relations in addition to postural data. Temporal relationships can help recognize activities with cyclic structure and are often implicit because plans have degrees of ordering actions. Relations with objects can help(More)
I. INTRODUCTION For robots to properly interact with humans, it is important that they are able to recognize users' plans and activities so that they may respond accordingly. Many activity recognition (AR) algorithms involve signal processing [1] or supervised learning [2], [3] to label raw sensor data with a human-defined action, but these methods restrict(More)
The 7th Symposium on Educational Advances in Artificial Intelligence (EAAI'17, co-chaired by Sven Koenig and Eric Eaton) launched the EAAI New and Future AI Educator Program to support the training of early-career university faculty, secondary school faculty, and future educators (PhD candidates or postdocs who intend a career in academia). As part of the(More)
Contemporary research in human-robot interaction (HRI) predominantly focuses on the user's experience while controlling a robot. However, with the increased deployment of artificial intelligence (AI) techniques, robots are quickly becoming more autonomous in both academic and industrial experimental settings. In addition to improving the user's interactive(More)