Dr. Henrik I. Christensen is the Qualcomm Chancellor's Chair of Robot Systems and a Distinguished Professor of Computer Science at Dept. of Computer Science and Engineering, UC San Diego. He is also the director of the Contextual Robotics Institute. He is an academic doing research on robotics and artificial intelligence, the main editor of the US National Robotics Roadmap, and an entrepreneur. Dr. Christensen does research on robotics and AI, with an emphasis on a systems view to problems. The research has been published in 350+ contributions across AI, Computer Vision, and Robotics. The research has been adopted by companies such as Electrolux, ABB, KUKA, Weda, BMW, Boeing, iRobot, PerMobil, General Motors. Henrik has been active in community organization such as the European Robotics Network and later as the main organizer of the US Robotics Roadmaps (2009, 2013, 2016, and 2020), which was the basis for the National Robotics Initiative (NSF, NIST, USDA, NIH). Dr. Christensen has co-founded several companies, including ROBO Global and Robust.AI. He serves as an advisor to companies and agencies across four continents. Dr. Christensen is a fellow of IEEE and AAAS. He was awarded the “Joseph Engelberger Award” 2011, the highest honor awarded by the industry, and named “Boeing Supplier of the Year” 2011. He was awarded an honorary doctorate (Dr. Techn. h.c.) in engineering from Aalborg University 2014. His work has been featured in major media such as CNN, BBC, NY Times, Financial Times, and Bloomberg.
Approximation and online algorithms for multidimensional bin packing: A survey
Christensen, H. I., Khan, A., Pokutta, S., & Tetali, P. (2017). Approximation and online algorithms for multidimensional bin packing: A survey. Computer Science Review, 24, 63–79. https://doi.org/10.1016/j.cosrev.2016.12.001
Towards life-long adaptive agents: Using metareasoning for combining knowledge-based planning with situated learning
Parashar, P., Goel, A. K., Sheneman, B., & Christensen, H. I. (2018). Towards life-long adaptive agents: Using metareasoning for combining knowledge-based planning with situated learning. The Knowledge Engineering Review, 33, e24. https://doi.org/10.1017/s0269888918000279
Graphical SLAM for Outdoor Applications
Folkesson, J., & Christensen, H. I. (2007). Graphical SLAM for Outdoor Applications. Journal of Field Robotics, 24(1-2), 51–70. https://doi.org/10.1002/rob.20174
Multi-scale assembly with robot teams
Dogar, M., Knepper, R. A., Spielberg, A., Choi, C., Christensen, H. I., & Rus, D. (2015). Multi-scale assembly with robot teams. The International Journal of Robotics Research, 34(13), 1645–1659. https://doi.org/10.1177/0278364915586606
Hierarchical rejection sampling for informed kinodynamic planning in high-dimensional spaces
Kunz, T., Thomaz, A., & Christensen, H. (2016). Hierarchical rejection sampling for informed kinodynamic planning in high-dimensional spaces. 2016 IEEE International Conference on Robotics and Automation (ICRA). https://doi.org/10.1109/icra.2016.7487120
Dr. Taylor received his A.B. degree in Electrical Computer and Systems Engineering from Harvard College in 1988 and his M.S. and Ph.D. degrees from Yale University in 1990 and 1994 respectively. Dr. Taylor was the Jamaica Scholar in 1984, a member of the Harvard chapter of Phi Beta Kappa and held a Harvard College Scholarship from 1986-1988. From 1994 to 1997 Dr. Taylor was a postdoctoral researcher and lecturer with the Department of Electrical Engineering and Computer Science at the University of California, Berkeley. He joined the faculty of the Computer and Information Science Department at the University of Pennsylvania in September 1997. He received an NSF CAREER award in 1998 and the Lindback Minority Junior Faculty Award in 2001. In 2012 he received a best paper award at the IEEE Workshop on the Applications of Computer Vision. Dr Taylor's research interests lie primarily in the fields of Computer Vision and Robotics and include: reconstruction of 3D models from images, vision-guided robot navigation and scene understanding. Dr. Taylor has served as an Associate Editor of the IEEE Transactions of Pattern Analysis and Machine Intelligence. He has also served on numerous conference organizing committees he is a General Chair of the International Conference on Computer Vision (ICCV) 2021 and was a Program Chair of the 2006 and 2017 editions of the IEEE Conference on Computer Vision and Pattern Recognition and of the 2013 edition of 3DV. In 2012 he was awarded the Christian R. and Mary F. Lindback Foundation Award for Distinguished Teaching at the University of Pennsylvania.
Mine Tunnel Exploration Using Multiple Quadrupedal Robots
Miller, I. D., Cladera, F., Cowley, A., Shivakumar, S. S., Lee, E. S., Jarin-Lipschitz, L., Bhat, A., Rodrigues, N., Zhou, A., Cohen, A., Kulkarni, A., Laney, J., Taylor, C. J., & Kumar, V. (2020). Mine Tunnel Exploration Using Multiple Quadrupedal Robots. IEEE Robotics and Automation Letters, 5(2), 2840–2847. https://doi.org/10.1109/lra.2020.2972872
Vision-based Multi-MAV Localization with Anonymous Relative Measurements Using Coupled Probabilistic Data Association Filter
Nguyen, T., Mohta, K., Taylor, C. J., & Kumar, V. (2020). Vision-based Multi-MAV Localization with Anonymous Relative Measurements Using Coupled Probabilistic Data Association Filter. 2020 IEEE International Conference on Robotics and Automation (ICRA). https://doi.org/10.1109/icra40945.2020.9196793
Depth Completion via Deep Basis Fitting
Qu, C., Nguyen, T., & Taylor, C. J. (2020). Depth Completion via Deep Basis Fitting. 2020 IEEE Winter Conference on Applications of Computer Vision (WACV). https://doi.org/10.1109/wacv45572.2020.9093349
The Open Vision Computer: An Integrated Sensing and Compute System for Mobile Robots
Quigley, M., Mohta, K., Shivakumar, S. S., Watterson, M., Mulgaonkar, Y., Arguedas, M., Sun, K., Liu, S., Pfrommer, B., Kumar, V., & Taylor, C. J. (2019). The Open Vision Computer: An Integrated Sensing and Compute System for Mobile Robots. 2019 International Conference on Robotics and Automation (ICRA). https://doi.org/10.1109/icra.2019.8794472
Robust Stereo Visual Inertial Odometry for Fast Autonomous Flight
Sun, K., Mohta, K., Pfrommer, B., Watterson, M., Liu, S., Mulgaonkar, Y., Taylor, C. J., & Kumar, V. (2018). Robust Stereo Visual Inertial Odometry for Fast Autonomous Flight. IEEE Robotics and Automation Letters, 3(2), 965–972. https://doi.org/10.1109/lra.2018.2793349
Dr. Vijay Kumar is currently a professor at the University of Pennsylvania. Robotics team co-lead and Associate Director, Translation; chair of Translation Committee. Nemirovsky Family Dean and Professor, School of Engineering and Applied Science. Founder of Exyn Technologies, Fellow of the ASME and IEEE, Elected Member of the National Academy of Engineering, American Philosophy Society, American Academy of Arts and Sciences. Engelberger Robotics Award, IEEE Robotics and Automation Pioneer and Field Awards.
Robust Fruit Counting: Combining Deep Learning, Tracking, and Structure from Motion
Liu, X., Chen, S. W., Aditya, S., Sivakumar, N., Dcunha, S., Qu, C., Taylor, C. J., Das, J., & Kumar, V. (2018). Robust Fruit Counting: Combining Deep Learning, Tracking, and Structure from Motion. 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). https://doi.org/10.1109/iros.2018.8594239
Counting Apples and Oranges with Deep Learning: A Data-Driven Approach
Chen, S. W., Shivakumar, S. S., Dcunha, S., Das, J., Okon, E., Qu, C., Taylor, C. J., & Kumar, V. (2017). Counting Apples and Oranges with Deep Learning: A Data-Driven Approach. IEEE Robotics and Automation Letters, 2(2), 781–788. https://doi.org/10.1109/lra.2017.2651944
Learning Decentralized Controllers for Robot Swarms with Graph Neural Networks
Tolstaya, E., Gama, F., Paulos, J., Pappas, G., Ribeiro, A., & Kumar, V. (2019). Learning Decentralized Controllers for Robot Swarms with Graph Neural Networks. Conference on Robot Learning.
Robust Stereo Visual Inertial Odometry for Fast Autonomous Flight
Sun, K., Mohta, K., Pfrommer, B., Watterson, M., Liu, S., Mulgaonkar, Y., Taylor, C. J., & Kumar, V. (2018). Robust Stereo Visual Inertial Odometry for Fast Autonomous Flight. IEEE Robotics and Automation Letters, 3(2), 965–972. https://doi.org/10.1109/lra.2018.2793349
Decentralization of Multiagent Policies by Learning What to Communicate
Paulos, J., Chen, S. W., Shishika, D., & Kumar, V. (2019). Decentralization of Multiagent Policies by Learning What to Communicate. 2019 International Conference on Robotics and Automation (ICRA). https://doi.org/10.1109/icra.2019.8793777
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