Michael P. Vitus 260 King St Unit 757
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1 Michael P. Vitus 260 King St Unit 757 San Francisco, CA Research Interests Stochastic optimization with application to probabilistic planning for robotics; Optimization; Control theoretic techniques in robotics; Large scale simultaneous localization and mapping; Education Stanford, CA PhD. in Aeronautics and Astronautics Hybrid System Controls Laboratory University of California at Berkeley Berkeley, CA Exchange Student in Electrical Engineering and Computer Sciences Stanford, CA Master of Science in Aeronautics and Astronautics Sept Dec /4.3 GPA Coursework: Classical and Modern Control Design, Nonlinear Control, Hybrid Systems, Classical Dynamics, Dynamics and Control of Spacecraft, Linear Dynamical Systems, Convex Optimization, Robotics, and Machine Learning Rensselaer Polytechnic Institute Troy, NY Bachelor of Science in Aeronautical and Mechanical Engineering (Dual Major) Aug May /4.0 GPA Minor in Computer Science Research Hybrid System Controls Laboratory March March 2012 Advisor: Professor Claire Tomlin Stochastic optimization with application to probabilistic motion planning in deterministic and stochastic environments First successful, real-time experimental demonstration of chance constrained control with uncertain constraint parameters and variables on a quadrotor vehicle navigating through a 3D environment Developed a new risk allocation method to augment controller optimization Design and development of the Stanford Testbed of Autonomous Rotorcraft for Multi-Agent Control (STARMAC) Motion planning for autonomous vehicles Perception algorithms for localization on computational constrained vehicles Mobile sensor networks Analyzing the interaction of collision avoidance algorithms for aircraft Carrier Phase Differential Global Positioning System (CDGPS) June March 2006 Advisor: Professor Andrew Ng Implemented CDGPS for an aerobatic helicopter Developed algorithms for multiple receivers Formulated a technique to use multiple receivers while the helicopter is performing aggressive rolling/pitching maneuvers Experience Postdoctoral Researcher March Present Advisor: Claire Tomlin Berkeley, CA Stochastic motion planning and control, optimization, distributed algorithms for large scale estimation
2 YCombinator Startup incubator 3% acceptance rate StartX Stanford student startup accelerator 10% acceptance rate June Present Mountain View, CA March Present Palo Alto, CA NASA Ames - Intelligent Robotics Group January January 2008 Mentor: Liam Pedersen Mountain View, CA Dark Navigation Project - Navigating under low lighting conditions Implemented hazard/obstacle avoidance methods Evaluating performance of different sensors Successfully demonstrated algorithms on over 500m of autonomous driving Course Assistant Led problem sessions, held office hours, and formulated homework solutions Engr209a - Analysis and Control of Nonlinear Systems, Winter 2007 Engr207b - Modern Control II, Spring 2006 AA242A - Classical Dynamics, Autumn 2005 Guest Lecturer (Prof. Jean-Claude Latombe) Taught a lecture on sensing, planning and control for autonomous quadrotor vehicles Projects CS225b - Robot Programming Autumn 2006 Dr. Kurt Konolige Implemented local navigation, Markov Localization, and a gradient based global path planner Successfully demonstrated the algorithms on a mobile robotic platform Machine Learning for Controlled Slides of a RC Car Autumn 2005 Professor Andrew Ng Developed a model of a R/C car s dynamics and implemented a Q-learning controller Successfully executed the desired circular trajectory while sliding Awards Aeronautics and Astronautics Fellowship 2004 Paul Hemke award, sponsored by AIAA 2003 Founders Award of Excellence - Rensselaer 4.0 Award - Rensselaer Rensselaer Medal for Achievement in Math and Science Scholarship Skills Languages: C/C++, Java, OpenGL Software: Matlab, Maple, SolidWorks Operating Systems: Linux, Windows Miscellaneous: Excellent troubleshooting and debugging skills, experience with robot operating system (ROS) and point cloud library (PCL)
3 Publications Journal [1] Michael P. Vitus*, Wei Zhang*, Alessandro Abate, Jianghai Hu, and Claire J. Tomlin. On efficient sensor scheduling for linear dynamical systems. Automatica, July *These authors contributed equally. [2] Jerry Ding*, Jeremy Gillula*, Haomiao Huang*, Michael P. Vitus*, Wei Zhang*, and Claire J. Tomlin. Toward reachability-based controller design for hybrid systems in robotics. IEEE Robotics & Automation Magazine, pages 33 43, September *These authors contributed equally. [3] Michael P. Vitus, Steven L. Waslander, and Claire J. Tomlin. Locally optimal decomposition for autonomous obstacle avoidance with the tunnel-milp algorithm. submitted to IEEE Transactions on Robotics, [4] Jeremy Gillula*, Gabriel M. Hoffmann*, Haomiao Huang*, Michael P. Vitus*, and Claire J. Tomlin. Applications of hybrid reachability analysis to robotic aerial vehicles. International Journal of Robotics Research, 30(3), March *These authors contributed equally. Proceedings [5] Michael P. Vitus and Claire J. Tomlin. A hybrid method for chance constrained control in uncertain environments. In Proceedings of the 51th IEEE Conference on Decision and Control, Maui, Hawaii, December [6] Michael P. Vitus, Wei Zhang, and Claire J. Tomlin. A hierarchical method for stochastic motion planning in uncertain environments. In IEEE/RSJ International Conference on Intelligent Robots and Systems, Algarve, Portugal, October [7] Mac Schwager, Michael P. Vitus, Daniela Rus, and Claire J. Tomlin. Robust adaptive coverage for robotic sensor networks. In Proceedings of the International Symposium on Robotics Research, Flagstaff, Arizona, August [8] Michael P. Vitus and Claire J. Tomlin. On feedback design and risk allocation in chance constrained programming. In Proceedings of the 50th IEEE Conference on Decision and Control, Orlando, Florida, December [9] Michael P. Vitus and Claire J. Tomlin. Belief space planning for linear, Gaussian systems in uncertain environments. In 18th World Congress of the International Federation of Automatic Control, Milan, Italy, September [10] Michael P. Vitus and Claire J. Tomlin. Closed-loop belief space planning for linear, Gaussian systems. In 2011 IEEE International Conference on Robotics and Automation, Shanghai, China, May [11] Michael P. Vitus, Wei Zhang, Alessandro Abate, Jianghai Hu, and Claire J. Tomlin. On sensor scheduling of linear dynamical systems with error bounds. In Proceedings of the 49th IEEE Conference on Decision and Control, Atlanta, Georgia, December [12] Wei Zhang, Michael P. Vitus, Jianghai Hu, Alessandro Abate, and Claire J. Tomlin. On the optimal solutions of the infinite-horizon linear sensor scheduling problem. In Proceedings of the 49th IEEE Conference on Decision and Control, Atlanta, Georgia, December [13] Michael P. Vitus and Claire J. Tomlin. Sensor placement for improved robotic navigation. In Proceedings of Robotics: Science and Systems, Zaragoza, Spain, June [14] Michael P. Vitus, Wei Zhang, Alessandro Abate, Jianghai Hu, and Claire J. Tomlin. On efficient sensor scheduling for linear dynamical systems. In Proceedings of the 2010 American Control Conference, Baltimore, Maryland, June [15] Jeremy Gillula*, Haomiao Huang*, Michael P. Vitus*, and Claire J. Tomlin*. Design of guaranteed safe maneuvers using reachable sets: Autonomous quadrotor aerobatics in theory and practice. In Proceedings of the 2010 IEEE International Conference on Robotics and Automation, Anchorage, Alaska, May *These authors contributed equally. [16] Wei Zhang, Alessandro Abate, Michael P. Vitus, and Jianghai Hu. On piecewise quadratic control-lyapunov functions for switched linear systems. In Proceedings of the 48th IEEE Conference on Decision and Control, Shanghai, China, December [17] Jeremy Gillula*, Haomiao Huang*, Michael P. Vitus*, and Claire J. Tomlin. Design and analysis of hybrid systems with applications to robotic aerial vehicles. In Proceedings of the 14th International Symposium of Robotics Research, Lucerne, Switzerland, September *These authors contributed equally.
4 [18] Michael P. Vitus, Steven L. Waslander, and Claire J. Tomlin. Locally optimal decomposition for autonomous obstacle avoidance with the tunnel-milp algorithm. In Proceedings of the 47th IEEE Conference on Decision and Control, Cancun, Mexico, December [19] Michael P. Vitus, Vijay Pradeep, Gabriel M. Hoffmann, Steven L. Waslander, and Claire J. Tomlin. Tunnel-MILP: Path planning with sequential convex polytopes. In Proceedings of the AIAA Guidance, Navigation, and Control Conference, Honolulu, Hawaii, August [20] Michael P. Vitus and Claire J. Tomlin. Hierarchical, hybrid framework for collision avoidance algorithms in the national airspace. In Proceedings of the AIAA Guidance, Navigation, and Control Conference and Exhibit, Honolulu, HI, August [21] Liam Pedersen, Chin San Han, and Michael P. Vitus. Dark navigation: Sensing and rover navigation in permanently shadowed lunar craters. In 9th International Symposium on Artificial Intelligence, Robotics and Automation in Space, Los Angeles, CA, February Thesis [22] Michael P. Vitus. Stochastic Control via Chance Constrained Optimization and its Application to Unmanned Aerial Vehicles. PhD thesis,, March Video [23] Gabriel M. Hoffmann, Steven L. Waslander, Michael P. Vitus, Haomiao Huang, Jeremy Gillula, Vijay Pradeep, and Claire J. Tomlin. Stanford testbed of autonomous rotorcraft for multi-agent control. IEEE/RSJ International Conference on Intelligent Robots and Systems, [24] Gabriel M. Hoffmann, Steven L. Waslander, Haomiao Huang, Vijay Pradeep, Michael P. Vitus, Jeremy Gillula, and Claire J. Tomlin. STARMAC: The stanford testbed of autonomous rotorcraft for multi-agent control. Association for the Advancement of Artificial Intelligence, Awarded: Best Demonstration Video. Seminars and Workshops (excluding conference talks) Workshop on 3D Exploration, Mapping, and Surveillance with Aerial Robots, Robotics Science and Systems (RSS), Los Angeles, California, June Stochastic Motion Planning, MIT, April Documentary on University of California at Berkeley, filmed by Fred Wiseman, October Hybrid Systems Control Conference, Stockholm, Sweden, April 2010 Workshop on Formal Methods in Robotics and Automation, IEEE International Conference on Robotics and Automation (ICRA), Kobe, Japan, Workshop on Bridging the gap between high-level discrete representations and low-level continuous behaviors, Robotics Science and Systems (RSS), Seattle, Washington, June Aeronautics and Astronautics 50th Year Anniversary,, May, Stanford High Performance Computing Conference III,, August, Academic Service Co-organizer of the workshop Stochastic Motion Planning and Information Based Control at the Robotics Science and Systems, Co-chair in the stochastic and control problems session at the International Federation of Automatic Control, 2011 Co-chair in the modeling and analysis of multi-agent systems session at the IEEE Conference on Decision and Control, 2008 Reviewer for:
5 Robotics Science and Systems (RSS) International Conference on Robotics and Automation (ICRA) IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) American Control Conference (ACC) IEEE Conference on Decision and Control (CDC) International Federation of Automatic Control (IFAC) AIAA Guidance, Navigation, and Control Hybrid Systems: Computation and Control (HSCC) IEEE Transactions on Automatic Control Systems & Control Letters Autonomous Robots
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