Abstract: Robots are becoming more and more popular with the rise of self driving cars, autonomous drones, and warehouse automation. However, they still require experts to set up the goals for the task, and are usually devoid of a high level understanding of its environment. Language can address these issues. Non expert users can seamlessly instruct robots using natural language commands. Linguistic resources can be used to extract knowledge about the world, which can be distilled into actionable intelligence. In this talk, I will describe some of our recent work in this direction. The first focuses on robust referring expression grounding, allowing users to describe commands involving objects in the environment. The second focuses on grounding high level instructions using background knowledge from WikiHow, Conceptnet and Wordnet. I will conclude by describing some of our ongoing work in acquiring commonsense knowledge for household robots.
Bio: Subhro is a Postdoctoral Associate at the Computer Science and AI Laboratory (CSAIL) at MIT working with Prof. Nicholas Roy. His research focuses on grounding natural language instructions and commonsense knowledge acquisition; aimed towards capable service robots that interact seamlessly with humans. His research contributes towards programs funded by the US Army Research Labs and the Toyota Research Institute.
Subhro obtained his Ph.D. at the University of Illinois, Urbana Champaign, advised by Prof. Dan Roth. His doctoral research focused on models for automated numeric reasoning and word problem solving. His research led to the development of several top performing word problem solvers and the MAWPS system for standardizing datasets and evaluation in the area. His work has been published in TACL, EMNLP, NAACL, AAAI, CoRL and ISER. Subhro obtained his B. Tech. degree at the Indian Institute of Technology (IIT) Kharagpur.