ECE Seminar Series Fall 2014

Thursday October 30^st 1-2 PM, ITEB 336

Passivity-Based Control and Estimation in Networked Robotics and Vision

Takeshi Hatanaka

Assistant Professor, Department of Mechanical and Control Engineering, Tokyo Institute of Technology

 

Abstract: This talk introduces a series of our research outcomes on passivity-based
estimation and control in networked robotics and vision. The former part discusses how passivity is utilized for visual feedback motion estimation and control. After pointing out inherent passivity in 3-D rigid-body motion, we present a passivity-based 3-D motion estimation mechanism, termed visual motion observer, and the observer-based camera control scheme. It is also shown that the presented framework can successfully incorporate other passive components like an object motion model and a manipulator dynamics while ensuring stability of the total system, owing to passivity preservation property w.r.t. feedback connections. The second part investigates passivity-based cooperative control and estimation. We first introduce a basic idea of synchronizing passive dynamical components under local interactions. Based on the approach, we then address 3-D motion coordination problems
of a network of rigid bodies. The presented results are also extended to flocking in three dimensions,
making use of the energy-based property of the passivity approach. Finally, we address visual feedback motion coordination and cooperative motion estimation, combining the ideas of the above two parts.
A book compiling the contents of this talk will be published in 2015 (expected).

 

Short Bio: Takeshi Hatanaka received B.Eng. degree in informatics and mathematical science, M.Inf.
and Ph.D. degrees in applied mathematics and physics all from Kyoto University, Japan in 2002, 2004 and 2007, respectively. He is currently an assistant professor in the Department of Mechanical and Control Engineering, Tokyo Institute of Technology, Japan. His research interests include cooperative control and estimation for robotic networks and visual sensor networks. He received Outstanding Research Award and Best Paper Award from SICE in 2014 and 2009, respectively.

 

Host: Ashwin Dani, Ashwin.dani@engr.uconn.edu

ECE Seminar Series Fall 2014

Thursday October 23^st, 1-2 PM, ITEB 336

Towards a formal design of distributed cooperative systems

 Hai Lin

Assistant Professor, Electrical Engineering, University of Notre Dame

 

 Abstract: A common challenge in our future engineered system design, such as power grids, intelligent transportation networks and flexible-manufacturing systems, is how to make a large number of distributed systems work together in a reliable and efficient manner. Existing methods are either only suitable for small scale systematic synthesis, oversimplifying the nodal dynamics, or fail to adapt to changing environments. This motivates our research aiming at a scalable, correct-by-construction formal design methodology for distributed cooperative systems. In particular, we focus on a formal design of multi-robot systems that can guarantee the accomplishment of high-level team missions through automatic synthesis of local coordination mechanisms and control laws. The basic idea is to decompose the team mission into individual subtasks such that the design can be reduced to local synthesis problems for individual robots. Multidisciplinary approaches combining hybrid systems, supervisory control, inference deduction and model checking are utilized to achieve this goal. The developed theory will enable robots in the team to cooperatively learn their individual roles in a mission, and then automatically synthesize local supervisors to fulfill their subtasks. A salient feature of the proposed method lies on its ability to handle environmental uncertainties and un-modeled dynamics as we do not require an explicit model of the transition dynamics of each agent and their interactions with the environment. In addition, the design is on-line and reactive enabling the robot team to adapt to changing environments and dynamic tasking.

 

Short Bio: Hai Lin obtained his B.S. degree at the University of Science and Technology Beijing and his M.S. degree from the Chinese Academy of Sciences in 1997 and 2000 respectively. In 2005, he received his Ph.D. degree from the University of Notre Dame. Dr. Lin is currently an Assistant Professor at the Department of Electrical Engineering, University of Notre Dame. Before returning to his alma mater, Hai has been working as an assistant professor in the National University of Singapore from 2006 to 2011. Dr. Lin’s teaching and research interests are in the multidisciplinary study of the problems at the intersections of control, communication, computation and life sciences. His current research thrust is on cyber-physical systems, multi-robot cooperative tasking, systems biology and hybrid control. Hai has been served in several committees and editorial board. He is the Program Chair for IEEE ICCA 2011, IEEE CIS 2011 and the Chair for IEEE Systems, Man and Cybernetics Singapore Chapter for 2009 and 2010. He is a recipient of 2013 NSF CAREER award and a senior member of IEEE.

 

 

Host: Peng Zhang, peng@engr.uconn.edu

Special ECE/CSE Seminar

Tuesday October 21^st 11 AM – 12 PM, ITEB 336

Challenges of Human-in-the-Loop Planning & Decision Support

Subbarao Kambhampati

Arizona State University

Abstract: Endowing  an automated agent with  the ability to “plan” — i.e., convert its high-level goals into an executable course of action — has been a long-standing quest in Artificial Intelligence.  For much of the history of automated planning, the dominant research theme has been efficient synthesis of plans under increasingly expressive system dynamics (classical, temporal, stochastic etc.).

 

An implicit assumption underlying  this research has been that the planner’s responsibilities start with taking a complete specification, and end with giving out a complete course of action. This assumption is no longer valid when humans are part of the decision making loop, as is the case in an increasing number of decision support and human-machine teaming scenarios.

In this talk I will identify the research challenges in human-in-the-loop planning, including the need to interpret the goals/intentions of the humans in the loop, the need to support continual planning and replanning, the need to unobtrusively support team-decision making, and above all the need to do handle pervasive incompleteness in the domain models as well as problem specification.  I will then describe some of our ongoing work in handling these challenges in the context of human-robot teaming and crowd-sourced planning.

 

Short Bio: Dr. Subbarao Kambhampati is a professor of Computer Science at Arizona State University, where he leads the Yochan research group focusing on the challenges in  automated planning and decision support, as well as information integration from structured and unstructured data sources.  He is a 1994 NSF Young Investigator, a 2004 IBM faculty fellow and thrice received Google Research Awards. He was elected fellow of AAAI (in 2004) for his contributions to automated planning. He received the 2002 college of engineering teaching excellence award, 2011 university last lecture invitation, and 2012 departmental best teacher award. Kambhampati was the co-chair of AAAI 2005, and will be the program chair of IJCAI 2016. He is an elected Trustee of IJCAI, and the president-elect of AAAI.

 

Host: Krishna Pattipati, krishna@engr.uconn.edu