Robotics Colloquia

Robotics Colloquium

The Robotics Colloquium features talks by invited and local researchers on all aspects of robotics, including control, perception, machine learning, mechanical design and interaction. The colloquium is held Fridays between 2:30-3:30pm. Special seminars outside this schedule are indicated with * below. Check schedule below for location. Refreshments are served.

If you would like to give a talk in upcoming Robotics Colloquia, please contact Maya Cakmak (mcakmakatcs). If you would like to get regular email announcements and reminders about the robotics colloquium speakers, please sign up to the Robotics@UW mailing list.

 
Spring 2017 Organizers: Aaron Walsman, Sam Burden, Maya Cakmak, Dieter Fox
03/31/2017
CSE 305
Richard Vaughan
Simon Fraser University
Simple, Robust Interaction Between Humans and Teams of Robots abstract
04/07/2017
CSE 691
Oussama Khatib
Stanford
Ocean One: A Robotic Avatar for Oceanic Discovery abstract
04/14/2017
CSE 305
Debadeepta Dey
Microsoft Research
Learning via Interaction for Machine Perception and Control abstract
04/21/2017
CSE 303 (11 AM)
Eric Eaton
University of Pennsylvania
Efficient Lifelong Machine Learning: an Online Multi-Task Learning Perspective abstract
04/21/2017
CSE 305
Katsu Ikeuchi
Microsoft Research
e-Intangible Heritage, from Dancing robots to Cyber Humanities abstract
04/28/2017
CSE 691
Henrik Christensen
UC San Diego
Object Based Mapping abstract
05/05/2017
CSE 305
Alberto Rodriguez
MIT
TBA abstract
05/12/2017
CSE 305
Charlie Kemp
Georgia Tech
TBA abstract
05/19/2017
CSE 305
Karol Hausman
University of Southern California
Rethinking Perception-Action Loops abstract
05/26/2017
 
TBA    
06/02/2017
 
No Colloquium (ICRA)    
 
Winter 2017 Organizers: Sam Burden, Maya Cakmak, Dieter Fox
01/06/2017
No colloquium    
01/13/2017
 
Matt Rueben
Oregon State University
Privacy Sensitive Robotics abstract
01/20/2017
2:30-5:00pm
Frontiers of Science
Savery Hall 260
01/27/2017
Ross Hatton
Oregon State University
TBA abstract
02/03/2017
Avik De
University of Pennsylvania
TBA abstract
02/10/2017
TBA    
02/17/2017
Sonia Chernova
Georgia Institute of Technology
Reliable Robot Autonomy through Learning and Interaction abstract
02/24/2017
TBA    
03/03/2017
TBA    
03/10/2017
TBA    
 
Fall 2016 Organizers: Sam Burden, Maya Cakmak, Dieter Fox, Sawyer Fuller
10/07/2016
CSE 305
David Remy
University of Michigan
Gaits and Natural Dynamics in Robotic Legged Locomotion abstract
10/14/2016
 
IROS 2016 and DUB retreat
No talk
   
10/21/2016
Industry Affiliates Week
Check out talks and posters by robotics students
   
10/28/2016
CSE 305
Emo Todorov
University of Washington
Goal-directed Dynamics abstract
11/04/2016
CSE 305
Sean Andrist
Microsoft Research
Gaze Mechanisms for Situated Interaction with Embodied Agents abstract
11/11/2016
 
Veterans day
No talk
   
11/18/2016
CSE 305
Nick Roy
MIT
Planning to Fly (and Drive) Aggressively abstract
11/25/2016
 
Thanksgiving
No talk
   
12/02/2016
CSE 305
Shai Revzen
University of Michigan
TBD abstract
12/09/2016
CSE 305
Ashis Banerjee
University of Washington
TBD abstract
 
Spring 2016 Organizers: Justin Huang, Leah Perlmutter, Dieter Fox, and Maya Cakmak
4/1/16
CSE 305
Tomás Lozano-Pérez
MIT
Integrated task and motion planning in belief space abstract
4/8/16
CSE 305
Henny Admoni
CMU / Yale
Recognizing Human Intent for Assistive Robotics abstract
4/11/16
CSE 305
Wolfram Burgard
University of Frieburg
Deep Learning for Robot Navigation and Perception abstract
4/22/16
CSE 305
Travis Deyle
Cobalt Robotics
RFID-Enhanced Robots Enable New Applications in Healthcare, Asset Tracking, and Remote Sensing abstract
5/6/16
CSE 305
Brian Scassellati
Yale
Robots That Teach abstract
5/13/16
CSE 305
Sarah Elliott, Mohammad Haghighipanah, Vikash Kumar, Yangming Li, Muneaki Miyasaka, Leah Perlmutter, Luis Puig, and Yuyin Sun
University of Washington
ICRA 2016 Practice Talks abstract
6/3/16
CSE 305
Sidd Srinivasa
CMU
Physics-based Manipulation abstract
*6/10/16
CSE 403
3:30 pm
Ashish Kapoor
Microsoft Research
Planetary Scale Swarm Sensing, Planning and Control for Weather Prediction abstract
 
Winter 2016 Organizers: Kendall Lowrey, Patrick Lancaster, and Dieter Fox
3/11/16
CSE 305
Daniel Butler
UW CSE
Model-based Reinforcement Learning with Parametrized Physical Models and Optimism-Driven Exploration abstract
3/04/16
CSE 305
James Youngquist
UW CSE
DeepMPC: Learning Deep Latent Features for Model Predictive Control abstract
2/26/16
CSE 305
Justin Huang
UW CSE
Place Recognition with ConvNet Landmarks: Viewpoint-Robust, Condition-Robust, Training-Free abstract
2/19/16
EEB 303
Daniel Gordon
UW CSE
Deep Neural Decision Forests abstract
2/12/16
CSE 305
Harley Montgomery
UW CSE
End-to-End Training of Deep Visuomotor Policies abstract
2/5/16
CSE 305
Aaron Walsman
UW CSE
Mastering the game of Go with deep neural networks and tree search abstract
1/29/16
CSE 305
Zachary Nehrenberg
UW CSE
Real-Time Trajectory Generation for Quadrocopters abstract
1/29/16
CSE 305
Patrick Lancaster
UW CSE
Towards Learning Hierarchical Skills for Multi-Phase Manipulation Tasks abstract
1/22/16
CSE 305
Tanner Schmidt
UW CSE
Pose Estimation of Kinematic Chain Instances via Object Coordinate Regression abstract
1/15/16
CSE 305
Kendall Lowrey
UW CSE
Combining the benefits of function approximation and trajectory optimization abstract
1/15/16
CSE 305
Vladimir Korukov
UW CSE
Information-Theoretic Planning with Trajectory Optimization for Dense 3D Mapping abstract
 
Fall 2015 Organizers: Tanner Schmidt and Dieter Fox
10/9/15
CSE 305
Dan Bohus
Microsoft Research
Physically Situated Dialog: Opportunities and Challenges abstract
10/16/15
CSE 305
Sawyer Fuller
UW
Aerial autonomy at insect scale: What flying insects can tell us about robotics and vice versa abstract
10/23/15
Kane Hall 110
Russ Tedrake
MIT
From Polynomials to Humanoid Robots
Part of the MathAcrossCampus Colloquium Series
abstract
10/30/15
CSE 305
Frank Dellaert
Skydio
Factor Graphs for Flexible Inference in Robotics and Vision abstract
11/6/15
CSE 305
Student Research Lightning Talks    
11/13/15
CSE 305
Louis-Philippe Morency
CMU
Modeling Human Communication Dynamics abstract
11/20/15
CSE 305
Tom Whelan
Oculus Research
Real-time dense methods for 3D perception abstract
11/27/15
CSE 305
Thanksgiving
No talk
   
12/4/15
CSE 305
Seth Hutchinson
UIUC
Robust Distributed Control Policies for Multi-Robot Systems abstract
12/11/15
CSE 305
Dmitry Berenson
WPI
Toward General-Purpose Manipulation of Deformable Objects abstract
 
Spring 2015 Organizers: Connor Schenck, Maya Cakmak, Dieter Fox
04/17/15
CSE 303
Neil Lebeck and Natalie Brace
UW CSE
Multirotor Aerial Vehicles: Modeling, Estimation, and Control of Quadrotor abstract
04/24/15
CSE 303
Peter Henry
UW CSE
LSD-SLAM: Large-Scale Direct Monocular SLAM abstract
05/01/15
CSE 303
Dan Butler
UW CSE
Probabilistic Segmentation and Targeted Exploration of Objects in Cluttered Environments abstract
05/07/15
CSE 303
Marc Deisenroth
Imperial College, London
Statistical Machine Learning for Autonomous Systems and Robots abstract
05/15/15
CSE 303
Arunkumar Byravan and Kendall Lowrey
UW CSE
Reinforcement Learning in Robotics: A Survey abstract
05/22/15   ICRA practice talks. abstracts
05/29/15 No Colloquium Colloquium cancelled for ICRA 2015.  
06/05/15
CSE 303
Jim Youngquist
UW CSE
A Strictly Convex Hull for Computing Proximity Distances With Continuous Gradients abstract
 
Winter 2015 Organizers: Connor Schenck, Maya Cakmak, Dieter Fox
01/14/15
CSE 305
Mike Chung
UW CSE
Accelerating Imitation Learning through Crowdsourcing abstract
  Tanner Schmidt
UW CSE
Dense Articulated Real-Time Tracking abstract
01/23/15
CSE 305
Discussion Amazon Picking Challenge <
01/30/15 No colloquium    
02/06/15
CSE 305
Joseph Xu
UW CSE
Design and Control of an Anthropomorphic Robotic Hand: Learning Advantages From the Human Body & Brain abstract
  Vikash Kumar
UW CSE
Dimensionality Augmentation: A tool towards synthesizing complex and expressive behaviors abstract
02/13/15
CSE 305
Sofia Alexandrova
UW CSE
RoboFlow: A Flow-based Visual Programming Language for Mobile Manipulation Tasks abstract
02/20/15
CSE 305
Igor Mordatch
UW CSE
Synthesis of Interactive Control for Diverse Complex Characters with Neural Networks abstract
02/27/15
CSE 305
Richard Newcombe
UW CSE
DynamicFusion: Reconstruction and Tracking of Non-Rigid Scenes in Real-Time abstract
03/06/15
CSE 691
Aaron Steinfeld
Carnegie Mellon University
Understanding and Creating Appropriate Robot Behavior abstract
03/13/15
CSE 305
Luis Puig
UW CSE
Overview of Omnidirectional Vision abstract
 
Autumn 2014 Organizers: Vikash Kumar, Maya Cakmak, Dieter Fox
10/03/14
CSE 305
Danny Kaufman
Adobe Creative Technologies Lab, Seattle
Geometric Algorithms for Computing Frictionally Contacting Systems abstract
10/10/14
EE 037
Dubi Katz & Michael Abrash
Oculus VR
VR, the future, and you abstract
10/17/14
CSE 503
3:30pm
Kira Mourao
PostDoc, Institute for Language, Cognition and Computation, University of Edinburgh
What happens if I push this button? Learning planning operators from experience abstract
10/24/14
CSE 305
Sam Burden
PostDoc, University of California, Berkeley
Hybrid Models for Dynamic and Dexterous Robots abstract
*10/29/14 (Wed)
HUB 250
12:30pm
Bilge Mutlu
University of Wisconsin, Madison
Human-Centered Principles and Methods for Designing Robotic Technologies
(Joint with DUB seminar, lunch will be served at 12:00)
abstract
10/31/14
CSE 305
Sergey Levine
PostDoc, University of California, Berkeley
Learning to Move: Machine Learning for Robotics and Animation abstract
11/07/14 No talk    
11/14/14 Sachin Patil
PostDoc, University of California, Berkeley
Coping with Uncertainty in Robotic Navigation and Manipulation abstract
11/21/14
Gates Commons
3:00pm
HRI Mini Symposium
HRI 2015 Program committee members
   
11/28/14 No talk, Thanksgiving Break    
12/05/14
CSE 305
Marianna Madry
Royal Institute of Technology (KTH), Sweden
Representing Objects in Robotics from Visual, Depth and Tactile Sensing abstract
*12/18/14 (Thu)
CSE 305
11:00am
Scott Niekum
Carnegie Mellon University
Structure Discovery in Robotics with Demonstrations and Active Learning abstract
Winter 2014, Organizer: Maya Cakmak
01/17/14
CSE 403
Byron Boots
UW CSE
Learning Better Models of Dynamical Systems abstract
01/24/14
CSE 403
Julie Shah
MIT
Integrating Robots into Team-Oriented Environments abstract
01/31/14
CSE 403
Ryan Calo
UW Law
Robotics & The New Cyberlaw abstract
02/07/14
CSE 403
James McLurkin
Rice University
Distributed Algorithms for Robot Recovery, Multi-Robot Triangulation, and Advanced Low-Cost Robots abstract
02/14/14   Cancelled  
02/21/14
CSE 403
Mihai Jalobeanu
Microsoft Research
Towards ubiquitous robots abstract
02/28/14
CSE 403
Cynthia Matuszek
UW CSE
Talking to Robots: Learning to Ground Human Language in Perception and Execution abstract
03/07/14   Cancelled  
03/14/14
CSE 403
Peter H. Kahn, Jr.
UW Psychology
Social and Moral Relationships with Robots abstract
03/21/14
Gates Commons
Gur Kimchi
Amazon
Amazon Prime Air abstract
Autumn 2013, Organizer: Maya Cakmak
10/11/13
MGH 241
Ashutosh Saxena
Cornell University
How should a robot perceive the world?
(Joint with Machine Learning)
abstract
10/18/13   UW/MSR Machine Learning day  
10/25/13
CSE 403
Kat Steele
University of Washington, Mechanical Engineering
Strategies for understanding and improving movement disorders abstract
11/01/13
CSE 403
Maya Cakmak
University of Washington, CSE
Towards seamless human-robot hand-overs abstract
*11/07/13 (Thu)
CSE 403
2:30-3:20pm
Ross A. Knepper
MIT
Autonomous Assembly In a Human World abstract
*11/08/13
CSE 403
12-1pm
Brian Ziebart
University of Illinois, Chicago
Beyond Conditionals: Structured Prediction for Interacting Processes
(Lunch will be served)
abstract
11/08/13
Gates Commons
Jenay Beer
University of South Carolina
Considerations for Designing Assistive Robotics to Promote Aging-in-Place abstract
11/15/13
CSE 403
Dinei Florencio
Microsoft Research
Navigation for telepresence robots and some thoughts on robot learning abstract
11/22/13
CSE 403
Andrzej Pronobis
University of Washington, CSE
Semantic Knowledge in Mobile Robotics: Perception, Reasoning, Communication and Actions abstract
12/06/13
Gates Commons
Steve Cousins
Savioke, Inc. & Willow Garage, Inc.
It's Time for Service Robots
(Joint with CSNE)
abstract
Spring 2013, Organizers: Cynthia Matuszek, Dieter Fox
04/5/13 Dieter Fox
Cynthia Matuszek
PechaKucha 20x20 for Robotics abstract
04/12/13 No talk    
04/19/13 Robotics Students & Staff PechaKucha-style Robotics Research Overviews abstract
04/26/13 Pete Wurman
Special Wednesday Colloquium, CSE 203
Coordinating Hundreds of Autonomous Vehicles in Warehouses
abstract
04/26/13 Matt Mason Learning to Use Simple Hands abstract
05/03/13 Nadia Shouraboura Canceled  
05/10/13 No talk (ICRA)
05/17/13 Tom Daniel Control and Dynamics of Animal Flight: Reverse Engineering Nature's Robots abstract
05/24/13 Katherine Kuchenbecker The Value of Tactile Sensations in Haptics and Robotics abstract
05/31/13 Pieter Abbeel Machine Learning and Optimization for Robotics abstract
06/07/13 Nick Roy Canceled  
Winter 2013, Organizer: Dieter Fox
01/18/13 Robotics and State
Estimation Lab
Overview of RSE Lab Research
01/25/13 Joshua Smith Robotics Research in the Sensor Systems Group abstract
02/01/13 no talk    
02/08/13 Gaurav Sukhatme Persistent Autonomy at Sea abstract
02/15/13 Jiri Najemnik Sequence Optimization in Engineering, Artificial Intelligence and Biology abstract
02/22/13 no talk    
03/01/13 Richard Newcombe Beyond Point Clouds: Adventures in Real-time Dense SLAM abstract
03/08/13 Tom Erez Model-Based Optimization for Intelligent Robot Control abstract
03/15/13 Byron Boots Spectral Approaches to Learning Dynamical Systems abstract
Spring 2012, Organizer: Dieter Fox
3/30/12 Andrea Thomaz Designing Learning Interactions for Robots abstract
4/6/12 Javier Movellan Towards a New Science of Learning abstract
4/13/12 Emanuel Todorov Automatic Synthesis of Complex Behaviors with Optimal Control abstract
4/20/12 Andrew Barto Autonomous Robot Acquisition of Transferable Skills abstract
4/27/12 Dieter Fox Grounding Natural Language in Robot Control Systems abstract
5/4/12 Allison Okamura Robot-Assisted Needle Steering abstract
5/11/12 Blake Hannaford Click the Scalpel -- Better Patient Outcomes by Advancing Robotics in Surgery abstract
5/18/12 no talk  
5/25/12 Malcolm MacIver Robotic Electrolocation abstract
6/1/12 Drew Bagnell Imitation Learning, Inverse Optimal Control and Purposeful Prediction abstract
 
DETAILED SCHEDULE FOR SPRING 2017
03/31/2017
CSE 305
Richard Vaughan
Simon Fraser University
Simple, Robust Interaction Between Humans and Teams of Robots
Abstract: Sensing technology for robots has improved dramatically in the last few years, but we do not see robots around us yet. How should robots behave around people and each other to get things done? My group works on behavioural strategies for mobile robots that exploit the new sensing capabilities, and allows them to perform sophisticated, robust interactions with the world and other agents. I’ll show videos of a series of novel vision-mediated Human-Robot Interactions with teams of driving and flying robots. At their best, the robots work like those in sci-fi movies. Others need more work, but the robots are always autonomous, the humans are uninstrumented, the interactions surprisingly simple, and we often work outdoors over long distances.

Speaker’s Bio: Richard Vaughan directs the Autonomy Lab at Simon Fraser University. His research interests include long-term autonomous robots, multi-robot systems, behavioural ecology, human-robot interaction (HRI), and robotics software. He demonstrated the first robot to control animal behaviour in 1998, co-created the Player/Stage Project in 2000, and recently showed the first uninstrumented HRI with UAVs. He currently serves on the Administrative Committee of the IEEE Robotics and Automation Society, and the editorial board of the Autonomous Robots journal, and is the Program Chair for IROS 2017.
04/07/2017
CSE 305
Oussama Khatib
Stanford University
Ocean One: A Robotic Avatar for Oceanic Discovery
Abstract: The promise of oceanic discovery has intrigued scientists and explorers for centuries, whether to study underwater ecology and climate change, or to uncover natural resources and historic secrets buried deep at archaeological sites. The quest to explore the ocean requires skilled human access. Reaching these depth is imperative since factors such as pollution and deep-sea trawling increasingly threaten ecology and archaeological sites. These needs demand a system deploying human-level expertise at the depths, and yet remotely operated vehicles (ROVs) are inadequate for the task. A robotic avatar could go where humans cannot, while embodying human intelligence and intentions through immersive interfaces. To meet the challenge of dexterous operation at oceanic depths, in collaboration with KAUST’s Red Sea Research Center and MEKA Robotics, we developed Ocean One, a bimanual force-controlled humanoid robot that brings immediate and intuitive haptic interaction to oceanic environments. Teaming with the French Ministry of Culture’s Underwater Archaeology Research Department, we deployed Ocean One in an expedition in the Mediterranean to Louis XIV’s flagship Lune, lying off the coast of Toulon at ninety-one meters. In the spring of 2016, Ocean One became the first robotic avatar to embody a human’s presence at the seabed. This expedition demonstrated synergistic collaboration between a robot and a human operating over challenging manipulation tasks in an inhospitable environment. Tasks such as coral-reef monitoring, underwater pipeline maintenance, and offshore and marine operations will greatly benefit from such robot capabilities. Ocean One’s journey in the Mediterranean marks a new level of marine exploration: Much as past technological innovations have impacted society, Ocean One’s ability to distance humans physically from dangerous and unreachable work spaces while connecting their skills, intuition, and experience to the task promises to fundamentally alter remote work. We foresee that robotic avatars will search for and acquire materials in hazardous and inhospitable settings, support equipment at remote sites, build infrastructure for monitoring the environment, and perform disaster prevention and recovery operations— be it deep in oceans and mines, at mountain tops, or in space.

Speaker’s Bio: Oussama Khatib received his PhD from Sup’Aero, Toulouse, France, in 1980. He is Professor of Computer Science at Stanford University. His research focuses on methodologies and technologies in human-centered robotics including humanoid control architectures, human motion synthesis, interactive dynamic simulation, haptics, and human-friendly robot design. He is a Fellow of IEEE. He is Co-Editor of the Springer Tracts in Advanced Robotics (STAR) series and the Springer Handbook of Robotics, which received the PROSE Award for Excellence in Physical Sciences & Mathematics. Professor Khatib is the President of the International Foundation of Robotics Research (IFRR). He has been the recipient of numerous awards, including the IEEE RAS Pioneer Award in Robotics and Automation, the IEEE RAS George Saridis Leadership Award in Robotics and Automation, the IEEE RAS Distinguished Service Award, and the Japan Robot Association (JARA) Award in Research and Development.
04/14/2017
CSE 305
Debadeepta Dey
Microsoft Research
Learning via Interaction for Machine Perception and Control
Abstract: As autonomous robots of all shapes and sizes proliferate in the world and start working in increasing proximity to humans it is critical that they produce safe intelligent behavior while efficiently learning from limited interactions in such computationally constrained regimes. A reoccurring problem is considering a limited number of actions from a very large number of possible actions. Examples include grasp selection in robotic manipulation, where the robot arm must evaluate a sequence of grasps with the aim of finding one which is successful as early on in the sequence as possible, or trajectory selection for mobile ground robots, where the task is to select a sequence of trajectories from a much larger set of feasible trajectories for minimising expected cost of traversal. A learning algorithm must therefore be able to predict a budgeted number of decisions which optimises a utility function of interest. Traditionally machine learning has focused on producing a single best prediction. We build an efficient framework for making multiple predictions where the objective is to optimise any utility function which is (monotone) submodular over a sequence of predictions. For each of these cases we optimise for the content and order of the sequence. We demonstrate the efficacy of these methods on several real world robotics problems. Another closely related problem is the budgeted information gathering problem, where a robot with a fixed fuel budget is required to maximise the amount of information gathered from the world, appears in practice across a wide range of applications in autonomous exploration and inspection with mobile robots. We present an efficient algorithm that trains a policy on the target distribution to imitate a clairvoyant oracle - an oracle that has full information about the world and computes non-myopic solutions to maximise information gathered. Additionally, our analysis provides theoretical insight into how to efficiently leverage imitation learning in such settings. Our approach paves the way forward for efficiently applying data-driven methods to the domain of information gathering.

Speaker’s Bio: Debadeepta Dey is a researcher in the Adaptive Systems and Interaction (ASI) group at Microsoft Research, Redmond, USA. He received his doctorate in 2015 at the Robotics Institute, Carnegie Mellon University, Pittsburgh, USA, where he was advised by Prof. J. Andrew (Drew) Bagnell. He does fundamental as well as applied research in machine learning, control and computer vision motivated by robotics problems. He is especially interested in bridging the gap between perception and planning for autonomous ground and aerial vehicles. His interests include decision-making under uncertainty, reinforcement learning, and machine learning. From 2007 to 2010 he was a researcher at the Field Robotics Center, Robotics Institute, Carnegie Mellon University.
04/21/2017
CSE 303 (11 AM)
Eric Eaton
University of Pennsylvania
Efficient Lifelong Machine Learning: an Online Multi-Task Learning Perspective
Abstract: Lifelong learning is a key characteristic of human intelligence, largely responsible for the variety and complexity of our behavior. This process allows us to rapidly learn new skills by building upon and continually refining our learned knowledge over a lifetime of experience. Incorporating these abilities into machine learning algorithms remains a mostly unsolved problem, but one that is essential for the development of versatile autonomous systems. In this talk, I will present our recent progress in developing algorithms for lifelong machine learning for classification, regression, and reinforcement learning, including applications to optimal control for robotics. These algorithms approach the problem from an online multi-task learning perspective, acquiring knowledge incrementally over consecutive learning tasks, and then transferring that knowledge to rapidly learn to solve new tasks. Our approach is highly efficient, scaling to large numbers of tasks and amounts of data, and provides a variety of theoretical guarantees. I will also discuss our work toward autonomous cross-domain transfer between diverse tasks, and zero-shot transfer learning from task descriptions.

Speaker’s Bio: Eric Eaton is a non-tenure-track faculty member in the Department of Computer and Information Science at the University of Pennsylvania, and a member of the GRASP (General Robotics, Automation, Sensing, & Perception) lab. Prior to joining Penn, he was a visiting assistant professor at Bryn Mawr College, a senior research scientist at Lockheed Martin Advanced Technology Laboratories, and part-time faculty at Swarthmore College. His primary research interests lie in the fields of machine learning, artificial intelligence, and data mining with applications to robotics, environmental sustainability, and medicine.
04/21/2017
CSE 305
Katsu Ikeuchi
Microsoft Research
e-Heritage Project Part I: e-Intangible Heritage, from Dancing robots to Cyber Humanities
Abstract: Tangible heritage, such as temples and statues, is disappearing day-by- day due to human and natural disaster. In-tangible heritage, such as folk dances, local songs, and dialects, has the same story due to lack of inheritors and mixing cultures. We have been developing methods to preserve such tangible and in-tangible heritage in the digital form. This project, which we refer to as e-Heritage, aims not only record heritage, but also analyze those recorded data for better understanding as well as display those data in new forms for promotion and education. This talk, the first talk of e-Heritage Project, covers our effort for handling in- tangible heritage. We are developing a method to preserve folk dances by the performance of dancing robots. Here, we follow the paradigm, learning-from- observation, in which a robot learns how to perform a dance from observing a human dance performance. Due to the physical difference between a human and a robot, the robot cannot exactly mimic the human actions. Instead, the robot first extracts important actions of the dance, referred to key poses, and then symbolically describes them using Labanotation, which the dance community has been using for recording dances. Finally, this labanotation is mapped to each different robot hardware for reconstructing the original dance performance. The second part tries to answer the question, what is the merit to preserve folk dances by using robot performance by the answer that such symbolic representations for robot performance provide new understandings of those dances. In order to demonstrate this point, we focus on folk dances of native Taiwanese, which consists of 14 different tribes. We have converted those folk dances into Labanotation for robot performance. Further, by analyzing these Labanotations obtained, we can clarify the social relations among these 14 tribes.

Speaker’s Bio: Dr. Katsushi Ikeuchi is a Principal Researcher of Microsoft Research Asia, stationed at Microsoft Redmond campus. He received a Ph.D. degree in Information Engineering from the University of Tokyo in 1978. After working at Artificial Intelligence Lab of Massachusetts Institute of Technology as a pos-doc fellows for three years, Electrotechnical Lab of Japanese Government as a researcher for five years, Robotics Institute of Carnegie Mellon University as a faculty member for ten years, Institute of Industrial Science of the University of Tokyo as a faculty member for nineteen years, he joined Microsoft Research Asia in 2015. His research interest spans computer vision, robotics, and computer graphics. He has received several awards, including IEEE-PAMI Distinguished Researcher Award, the Okawa Prize from the Okawa foundation, and Si-Ju- Ho-Sho (the Medal of Honor with Purple ribbon) from the Emperor of Japan. He is a fellow of IEEE, IEICE, IPSJ, and RSJ.
04/28/2017
CSE 305
Henrik Christensen
UC San Diego
Object Based Mapping
Abstract: To build mobile systems that can operate autonomously it is necessary to endow them with a sense of location. One of the basic aspects of autonomy is the ability to not get lost. How can we build robots that acquire a model of the surrounding world and utilize these models to achieve their mission without getting lost along the way. Simultaneous Localization and Mapping (SLAM) is widely used to provide the mapping and localization compete to robots. The process has three facets: extraction of features from sensor data, association of features with prior detected structures and estimation of position/pose and update of the map to make it current. The estimation part of the process is today typically performed using graphical models to allow for efficient computations and enable flexible handling of ambiguous situations. Over time the feature extraction has matured from use of basic features such as lines and corners to utilization of significant structures such as man-made objects (building, chairs, tables, cars, ...) that are easily identifiable. The discriminative nature of major structures simplifies data-association and facilities more efficient loop-closing. In this presentation we will discuss our modular mapping framework - OmniMapper - and how it can be utilized across a range of different applications for efficient computing. We will discuss a number of different strategies for object detection and pose estimation and also provide examples of mapping across a number of different sensory modalities. Finally we will show a number of examples of use of the OmniMapper across in- and out-door settings using air and ground vehicles.

Speaker’s Bio: Dr. Henrik I. Christensen is a Professor in Dept. of Computer Science and Engineering, UC San Diego. He is also the director of the Institute for Contextual Robotics. Prior to UC San Diego he was the founding director of Institute for Robotics and Intelligent machines (IRIM) at Georgia Institute of Technology (2006-2016). Dr. Christensen does research on systems integration, human-robot interaction, mapping and robot vision. The research is performed within the Cognitive Robotics Laboratory. He has published more than 350 contributions across AI, robotics and vision. His research has a strong emphasis on "real problems with real solutions". A problem needs a theoretical model, implementation, evaluation, and translation to the real world. He is actively engaged in the setup and coordination of robotics research in the US (and worldwide). Dr. Christensen received the Engelberger Award 2011, the highest honor awarded by the robotics industry. He was also awarded the "Boeing Supplier of the Year 2011". Dr. Christensen is a fellow of American Association for Advancement of Science (AAAS) and Institute of Electrical and Electronic Engineers (IEEE). He received an honorary doctorate in engineering from Aalborg University 2014. He collaborates with institutions and industries across three continents. His research has been featured in major media such as CNN, NY Times, BBC, ...
05/19/2017
CSE 305
Karol Hausman
University of Southern California
Rethinking the Action Perception Loops
Abstract: While perception has traditionally served action in robotics, it has been argued for some time that intelligent action generation can benefit perception, and carefully coupling perception with action can improve the performance of both. In this talk, I will report on recent progress in model-based and learning-based approaches that address aspects of the problem of closing perception-action loops. The first part of my talk will focus on a model-based, active perception technique that optimizes trajectories for self-calibration. This method takes into account motion constraints and produces an optimal trajectory that yields fast convergence of estimates of the self-calibration states and other user-chosen states. In the second part of my talk, I will present a deep reinforcement learning framework that learns manipulation skills on a real robot in a reasonable amount of time. The method handles contact and discontinuities in dynamics by combining the efficiency of model-based techniques and the generality of model-free reinforcement learning techniques.

Speaker’s Bio: Karol Hausman is a Ph.D. student at the University of Southern California in the Robotic Embedded Systems Lab under the supervision of Prof. Gaurav S. Sukhatme. His research interests lie in the field of interactive perception, reinforcement learning, and state estimation in robotics. He received his B.E. and M.E. degrees in Mechatronics from the Warsaw University of Technology, Poland, in 2010 and 2012, respectively. In 2013 he graduated with an M.Sc. degree in Robotics, Cognition and Intelligence from the Technical University Munich. During his Ph.D., he interned with Bosch Research Center Palo Alto, NASA JPL, Qualcomm Research and he will join Google DeepMind for an internship this Summer.

Details of previous Robotics Colloquia can be found here.