# Edwin Olson

Edwin Olson (born 3 May 1977) is an American computer scientist and an Associate Professor of Computer Science and Engineering at the University of Michigan. He is the director of the APRIL robotics lab, which studies Autonomy, Perception, Robotics, Interfaces, and Learning. He is also CEO of May Mobility, LLC., which develops driverless shuttle vehicles.

## Early life

Olson was born Edwin Brock Olson on 3 May 1977, and his birth was registered in Hennepin County, Minnesota. Olson was born to Dorothy Elaine Brock and Ebert Duane Olson of Bloomington Minnesota and was named after his paternal grandfather. Olson grew up in nearby Bloomington.

## Education

Olson attended JF Kennedy High School in Bloomington MN where he was captain of the math team, a student attorney for the state finalist mock trial team, an editor of the school yearbook, captain of the quiz bowl team, and co-founder of a school newspaper He graduated from the Massachusetts Institute of Technology in 2000 with a Bachelor of Science in Electrical Engineering and Computer Science. In 2001, Olson gained a Master of Engineering in Electrical Engineering and Computer Science at the Massachusetts Institute of Technology, where his thesis was “Otto: A Low-Cost Robotics Platform for Research and Education” and was advised by Lynn Andrea Stein (then Associate professor in the EECS Department and at the AI Laboratory and the Laboratory for Computer Science). In 2008 Olson was awarded a PhD in Computer Science and Engineering 2008 at the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) His thesis was Robust and Efficient Robotic Mapping . Olson was Advised by John J. Leonard (Professor of Mechanical and Ocean Engineering) and Seth J. Teller (Professor of Computer Science and Engineering). As of December 2024 the thesis has 90 citations. His research focused on scalable Simultaneous localization and mapping (SLAM) algorithms and SLAM-aware exploration.

## Honors and awards

Olson received the Morris Wellman Faculty Development Assistant Professor 2014 which is awarded to a junior faculty member in Computer Science and Engineering to recognize outstanding contributions to teaching and research. University of Michigan
Olson received the DARPA Young Faculty Award 2013 for Mutual Modeling for Human/Robot Teaming with Minimal Communications. It was established to identify and engage with rising research stars in junior faculty positions across US academic institutions. The award included access to the Muscatatuck Urban Training Center (MUTC) near Butlerville, Indiana, a 1,000-acre urban training facility used by DARPA for developmental and evaluation testing. “Muscatatuck is an amazing site for experimental robotics work—I can’t wait to bring my research there,” said Edwin Olson, before announcing that he intended to return to the facility in August 2014 for testing and evaluation of autonomous systems he is developing through his DARPA award in Supervised Autonomy.
Olson received the Frederick C. Hennie III Teaching Award for Teaching Excellence whilst at the MIT Department of Electrical Engineering and Computer Science.. Frederick C. Hennie III was Professor Emeritus in the Department of Electrical Engineering and Computer Science (EECS) until his death on October 23rd, 2023. He had served as a full professor in the department since 1968 and an Executive Officer for 25 years from 1971.
Olson received the New Enterprise Forum Entrepreneur of the Year from The Michigan Venture Capital Association in their 17th awards year. “[The award] is given to an individual who is not only changing the world in a good way through their entrepreneurial accomplishments, but is also inspiring others with their vision, leadership and achievements.” The award was established to recognize founders of Michigan-based, venture-backed companies that are a notable part of the State’s entrepreneurial community.

## Professional career

Edwin Olson has been undertaking key research into autonomous vehicle systems, in association with the University of Michigan and Toyota Research Institute of Ann Arbor throughout his academic and professional career.
Olson first addressed the challenge of autonomous vehicles when a grad student, joining an MIT team for MIT’s 2007 DARPA Urban Challenge competition, finishing 4th of six finishers. The competition was a 96 km (60 mi) urban area course, which was to be completed autonomously in less than 6 hours. Competitors had to obey all traffic regulations whilst negotiating with other traffic and obstacles and merging into traffic as required. As part of Track A of the competition, MIT received US $1 million in funding.
In 2010 Olson led Team Michigan (a collaboration between the University of Michigan's APRIL Lab and Soar Technology, Inc of Ann Arbor MI) to first place in the MAGIC 2010 robotics competition. The Multi Autonomous Ground-robotic International Challenge (MAGIC 2010) was jointly sponsored by the Australian and US Department of Defence. It required teams of robots to act collaboratively in order to perform reconnaissance and dynamic mapping exercises within a 250,000m2 urban indoor/outdoor environment. The robots needed to recognize and log interesting objects with minimal human intervention. Michigan entered the largest team consisting of 14 robots, with Team Michigan winning the first prize of $750,000. Key challenges included penalties for inaccurate dead-reckoning information, access to limited communications methods, and identifying and moving lethal obstacles. Olson’s team were noted for their ability to maintain consistent coordinate frames and elicite critically useful information from the human operators while simultaneously minimizing the human workload.
In a 2016 interview with Brad Plumer of VOX, Olson described four key tasks that fully self-driving cars would need to demonstrate:
1) understanding the environment around them;
2) understanding why the people they encounter on the road are behaving the way they are;
3) deciding how to respond when the action protocol depends on factors like the order in which the vehicle arrives at a junction; and 4) communicating with other people/vehicles. Olson went on to explain that reliability is the biggest challenge, “Humans aren’t perfect, but we’re amazingly good drivers when you think about it, with 100 million miles driven for every fatality… a robot system has to perform at least at that level.” He added that adverse weather is another variable but that he believed it was not a fundamental challenge. “Even if you had a car that only worked in fair weather, that’s still enormously valuable.” Olson also addressed the impact of the common interest in the customization of personal vehicles where even simple changes such as altering the wheel sizes could distort the vehicle’s decision-making abilities, “It’s hard to stop anyone from doing that.”
Olson also commented on the need for standards for V2X or Vehicle-to-everything communications that can enhance safety by allowing equipped vehicles to communicate hazards and events, but that there is a need for authentication of such messages to enhance trust and safety.
When others in the industry were predicting the imminent arrival of fully autonomous vehicles, Olson was more cautious “I’m skeptical that you’ll be able to buy a car in 2020 that you can just put your kid in and ship off to school. That kind of complete trust and autonomy is a ways off”, adding that “limited forms of autonomy are very plausible.” Examples were very low speed transportation and automated parking. In fact current ride hailing robotaxi's such as Waymo place a 17+ age requirement on riders that are unaccompanied by adults.
The Toyota Research Institute of North America (TRINA) announced in early 2016 that they were establishing a new facility at Ann Arbor Michigan to join their existing facilities at Stanford and MIT. As part of a $1 billion venture investment intended to accelerate autonomous vehicle technology, they recruited Professors Ryan Eustice and Edwin Olson, who would retain part-time faculty positions at University of Michigan, and committed $22M of initial funding to develop the Mcity test facility located on the North Campus of The University of Michigan. Olson was also Associate Professor of Computer Science and Engineering and director of the APRIL Robotics Lab. Olson commented, ”Sensor hardware and algorithms are improving at a tremendous pace. TRI researchers will push the frontier even further, resulting in safer vehicles and more helpful robots in the home.” Initially there would be a staff of 15, with a target of 50.. TRINA has filed around 1200 patents since 2008
In 2017 Olson delivered a keynote on Reliability and Robustness of Autonomous Systems at an EEE/RSJ International Conference on Intelligent Robots and Systems in Vancouver, BC, Canada. He addressed the gap between demo and real-world deployment for autonomous vehicles, when he explained that reliability wasn’t a simple case of eliminating bugs and working boundary conditions but rather a gulf that drives a need for fundamentally different ways of building these systems.
In January 2017 Edwin Olson, along with Allsyn Malek and Steve Vozar founded May Mobility (https://maymobility.com/meet-may/_ ), located in Ann Arbor, Michigan. May Mobility was established to develop autonomous technologies that provide transportation solutions for cities, campuses and similar environments targeted towards municipal and corporate requirements. As a safety first solution it uses a proprietary Multi-Policy Decision Making (MPDM) system as the core of its product.
By the end of 2024, May claimed it had completed more than 400,000 autonomy-enabled rides in public transit applications in the US and Japan. NTT is a key investor and May Mobility utilises partner Toyota’s Sienna Autono-MaaS (Mobility as a service) vehicle, including some customized with ADA-compliant wheelchair ramps and audio and visual cues within the vehicle to boost accessibility.
In episode #196 of Brandon Bartnick’s Future of Mobility podcast
The key, Olson said, was using the right vehicle for the right population density in ordeer to provide effective autonomous transportation. As a municipal transportation solution May is aiming to sign long term contracts with cities and corporations that would provide a guaranteed revenue stream and highly predictable demand, in comparison with the robotaxi approach of relying on speculative rider revenue.

### Patents

Patents (USPTO and Espacenet
* 11,269,332. Multi-perspective system and method for behavioral policy selection by an autonomous agent. Vozar, Olson, Voorheis. Mar 8, 2022.
* 11,269,331. Multi-perspective system and method for behavioral policy selection by an autonomous agent. Vozar, Olson, Voorheis. Mar 8, 2022.
* 11,352,023. Method and system for dynamically curating autonomous vehicle policies. Fairley, Ranjan, Kothbauer, Patel, Voorheis, Sterniak, Olson. June 7, 2022.
* 11,378,399. -performance inertial measurement using a redundant array of inexpensive inertial sensors. Wang, Olson. July 5, 2022.
* 11,472,436. Method and system for operating an autonomous agent with incomplete environmental information. Patel, Johnson, Meyer, Olson. October 18, 2022.
* 11,472,444. Method and system for dynamically updating an environmental representation of an autonomous agent. Goeddel, Johnson, Kothbauer, Sterniak, Voorheis, Olson. October 18, 2022.
* 11,513,189. Systems and methods for intelligently calibrating infrastructure devices using onboard sensors of an autonomous agent. Voorheis, Goeddel, Vozar, Olson. November 29, 2022.
* 11,525,887. Systems and methods for intelligently calibrating infrastructure devices using onboard sensors of an autonomous agent. Voorheis, Goeddel, Vozar, Olson. December 2022.
* 11,565,717. Method and system for remote assistance of an autonomous agent. Kothbauer, Sterniak, Olson. January 2022.
* 11,565,716. Method and system for dynamically curating autonomous vehicle policies. Fairley, Ranjan, Kothbauer, Patel, Voorheis, Sterniak, Olson. January 2022.
* US Patent 11,087,200 . Method and apparatus for constructing informative outcomes to guide multi- policy decision making. E Olson, D Mehta, G Ferrer. 2021.
* US Patent 10,803,745. Systems and methods for implementing multimodal safety operations with an autonomous agent. S Vozar, E Olson, S Messenger, C Johnson. 2020.
* US Patent 10,969,470. Systems and methods for intelligently calibrating infrastructure devices using onboard sensors of an autonomous agent. T Voorheis, R Goeddel, S Vozar, E Olson. 2019.
* US Patent 10,564,641 ; 10,962,975 ; 10,962,974 . Multi-perspective system and method for behavioral policy selection by an autonomous agent. S Vozar, E Olson, T Voorheis. 2019.
* US Patent 10,948,584 . Latent Oscillator Frequency Estimation For Ranging Measurements. E Olson, M Sean, J Mamish. 2018.
* US Patent 10,838,065 . Localization using 2D maps which capture vertical structures in 3D point data. E Olson, C Kershaw. 2018.
* US Patent 10,614,709 . Systems and methods for implementing multimodal safety operations with an autonomous agent. S Vozar, E Olson, S Messenger, C Johnson. 2019.
* US Patent 10,546,499 . Systems and methods for notifying an occupant of a cause for a deviation in a vehicle. J Marcoux, E Olson. 2017.
* US Patent 10,489,663 . Systems and methods for identifying changes within a mapped environment. E Olson, M James, R Eustice, R Wolcott. 2017.
* US Patent 10,460,053 . Systems and methods for surface property identification using waveform clas- sification. E Olson, M James, R Eustice. 2017.
* US Patent 10,210,672 . Systems and methods for remotely controlling data collection by a vehicle. M James, E Olson. 2017.
* US Patent 9,934,688 . Vehicle trajectory determination. E Olson, E Galceran, A Cunningham, R Eustice, J McBride. 2015.
* US Patent 9,811,760 . Online per-feature descriptor customization. A Richardson, E Olson. 2017.
* US Patent 9,618,938 . Field-based torque steering control. E Olson, E Galceran, RM Eustice, JR
McBride. 2017.
* US Patent 9,282,326 Interactive camera calibration tool. EB Olson, J Strom, A Richardson. 2016.
* US Utility Patent 7,457,800 . Storage system for randomly named blocks of data. NH Margolus, E Olson, M Sclafani, CJ Coburn, M Fortson. 2005.

## Personal life

Olson first explored programming using an Apple IIGS personal computer, initially using BASIC and then in 65816 assembler language. From 1992 he wrote and co-wrote a number of small applications and he credits that experience with building an enduring interest in computer architecture and algorithms.
Olson says has been playing the violin since the age of five and although he admits to being inconsistently devoted to the instrument, he has previously played with the Greater Twin Cities Youth Symphonies. He then played with the MIT Symphony Orchestra and was at one time concertmaster at the Cambridge Symphony Orchestra in Massachusetts. He joined the Ypsilanti Symphony Orchestra as a violinist in 2011 and has served as concertmaster there since 2013. In addition to his orchestral work, Olson performs informally and infrequently with varioud chamber ensembles. He plays a violin that was created by renowned Canadian violin maker Joseph Curtin, now of Ann Arbor Michigan, who is recognised as one of the great contemporary violin makers.

### Contributions to technical articles and journals

* Ryan J. Marcotte, Xipeng Wang, Dhanvin Mehta and Edwin Olson. Optimizing Multi-Robot Communication under Bandwidth Constraints. Autonomous Robots 2019.
* Markus P. Nemitz, Ryan J. Marcotte, Mohammed E. Sayed, Gonzalo Ferrer, Alfred O. Hero, Ed- win Olson and Adam A. Stokes. Multi-Functional Sensing for Swarm Robots Using Time Sequence Classification: HoverBot, an Example. Frontiers in Robotics and AI 2018.
* Markus P. Nemitz, Mohammed E. Sayed, John Mamish, Gonzalo Ferrer, Lijun Teng, Ross M. McKenzie, Alfred O. Hero, Edwin Olson and Adam A. Stokes. HoverBots: Precise Locomotion Using Robots That Are Designed for Manufacturability. Frontiers in Robotics and AI 2017.
* Enric Galceran, Alexander G. Cunningham, Ryan M. Eustice and Edwin Olson. Multipolicy decision-making for autonomous driving via changepoint-based behavior prediction: Theory and ex- periment. Autonomous Robots 2017.
* Edwin Olson and Pratik Agarwal. Inference on networks of mixtures for robust robot mapping. International Journal of Robotics Research 2013.
* Edwin Olson, Johannes Strom, Robert Goeddel, Ryan Morton, Pradeep Ranganathan and Andrew Richardson. Exploration and Mapping with Autonomous Robot Teams. Communications of the ACM 2013.
* Edwin Olson, Johannes Strom, Ryan Morton, Andrew Richardson, Pradeep Ranganathan, Robert Goeddel, Mihai Bulic, Jacob Crossman and Bob Marinier. Progress towards multi-robot reconnaissance and the MAGIC 2010 Competition. Journal of Field Robotics 2012.
* Yangming Li and Edwin Olson. A General Purpose Feature Extractor for Light Detection and Ranging Data. Sensors 2010.
* Albert S. Huang, Matthew Antone, Edwin Olson, Luke Fletcher, David Moore, Seth Teller and John Leonard. A High-rate, Heterogeneous Data Set from the DARPA Urban Challenge. International Journal of Robotics Research 2010.
* Edwin Olson. Recognizing Places using Spectrally Clustered Local Matches. Robotics and Au- tonomous Systems 2009.
* Albert Huang, David Moore, Matthew Antone, Edwin Olson and Seth Teller. Finding multiple lanes in urban road networks with vision and lidar. Autonomous Robots 2009.
* J. Leonard, J. How, S. Teller, M. Berger, S. Campbell, G. Fiore, L. Fletcher, E. Frazzoli, A. Huang, S. Karaman, O. Koch, Y. Kuwata, D. Moore, E. Olson, S. Peters, J. Teo, R. Truax, M. Walter, D. Barrett, A. Epstein, K. Maheloni, K. Moyer, T. Jones, R. Buckley, M. Antone, R. Galejs, S. Krishnamurthy and J. Williams. A Perception Driven Autonomous Urban Vehicle. Journal of Field Robotics 2008.
* Luke Fletcher, Seth Teller, Edwin Olson, David Moore, Yoshiaki Kuwata, Jonathan How, John Leonard, Isaac Miller, Mark Campbell, Dan Huttenlocher, Aaron Nathan and Frank-Robert Kline. The MIT – Cornell Collision and Why it Happened. Journal of Field Robotics Special Issue on the DARPA Urban Challenge 2008.
* Edwin Olson. Robust Dictionary Attack of Short Simple Substitution Ciphers. Cryptologia 2007. [15] Edwin Olson, John Leonard and Seth Teller. Robust Range-Only Beacon Localization. IEEE Journal of Oceanic Engineering 2006.
Refereed Conferences
* Edwin Olson. AXLE: Computationally-efficient trajectory smoothing using factor graph chains. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) 2021.
* Acshi Haggenmiller, Cameron Kabacinski, Maximilian Krogius and Edwin Olson. The Masked Mapper: Masked Metric Mapping. Proceedings of the IEEE/RSJ International Conference on Intelli- gent Robots and Systems (IROS) 2020.
* Maximilian Krogius, Acshi Haggenmiller and Edwin Olson. Flexible Layouts for Fiducial Tags. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2019.
* Acshi Haggenmiller, Maximilian Krogius and Edwin Olson. Non-parametric Error Modeling for Ultra-wideband Localization Networks. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) 2019.
* Xipeng Wang, Ryan J. Marcotte and Edwin Olson. GLFP: Global Localization from a Floor Plan. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2019.
* Xipeng Wang, Ryan Marcotte, Gonzalo Ferrer and Edwin Olson. AprilSAM: Real-time Smoothing and Mapping. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) 2018.
* Dhanvin Mehta, Gonzalo Ferrer and Edwin Olson. Backprop-MPDM: Faster risk-aware policy evaluation through efficient gradient optimization. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) 2018.
* Dhanvin Mehta, Gonzalo Ferrer and Edwin Olson. Fast discovery of influential outcomes for risk- aware MPDM. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) 2017.
* Xipeng Wang, Steve Vozar and Edwin Olson. FLAG: Feature-based Localization between Air and Ground. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) 2017.
* Robert Goeddel, Carl Kershaw, Jacopo Serafin and Edwin Olson. FLAT2D: Fast Localization from Approximate Transformation into 2D. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2016.
* Dhanvin Mehta, Gonzalo Ferrer and Edwin Olson. Autonomous Navigation in Dynamic Social Environments using Multi-Policy Decision Making. Proceedings of the IEEE/RSJ International Con- ference on Intelligent Robots and Systems (IROS) 2016.
* Robert Goeddel and Edwin Olson. Learning Semantic Place Labels from Occupancy Grids using CNNs. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2016.
* John Wang and Edwin Olson. AprilTag 2: Efficient and robust fiducial detection. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2016.
* Ryan Marcotte and Edwin Olson. Adaptive forward error correction with adjustable-latency QoS for robotic networks. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) 2016.
* Julie Bateman, Dimitrios Zekkos, Edwin Olson, Sean M. Messenger, Carl Kershaw, Xunchang Fei and Jerry Lynch. Preliminary Observations from Robot-Enabled Surface Methane Concentration Monitoring at a MSW Landfill. Geo-Chicago 2016 2016.
* Surat Kwanmuang and Edwin Olson. Maximum Likelihood Tracking of a Personal Dead-Reckoning System. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2015.
* Andrew Richardson and Edwin Olson. TailoredBRIEF: Online Per-Feature Descriptor Customiza- tion. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2015.
* Enric Galceran, Edwin Olson and Ryan M. Eustice. Augmented vehicle tracking under occlusions for decision-making in autonomous driving . Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) 2015 .
* John Wang and Edwin Olson. High-Performance Inertial Measurements Using a Redundant Array of Inexpensive Gyroscopes (RAIG). Proceedings of the IEEE Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI) 2015.
* Enric Galceran, Alexander G. Cunningham, Ryan M. Eustice and Edwin Olson. Multipolicy Decision-Making for Autonomous Driving via Changepoint-based Behavior Prediction. Proceedings of Robotics: Science and Systems (RSS) 2015.
* Edwin Olson. M3RSM: Many-to-Many Multi-Resolution Scan Matching. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) 2015.
* Alexander G. Cunningham, Enric Galceran, Ryan M. Eustice and Edwin Olson. MPDM: Multi- policy Decision-Making in Dynamic, Uncertain Environments for Autonomous Driving. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) 2015.
* Enric Galceran, Ryan M. Eustice and Edwin Olson. Toward integrated motion planning and control using potential fields and torque-based steering actuation for autonomous driving . Proceedings of the IEEE Intelligent Vehicle Symposium 2015 .
* Pradeep Ranganathan and Edwin Olson. Locally-weighted Homographies for Calibration of Imag- ing Systems. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2014.
* Andrew Richardson and Edwin Olson. PAS: Visual Odometry with Perspective Alignment Search. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2014.
* John Wang and Edwin Olson. Robust Pose Graph Optimization Using Stochastic Gradient De- scent. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) 2014.
* Andrew Richardson, Johannes Strom and Edwin Olson. AprilCal: Assisted and repeatable camera calibration. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2013.
* Lauren Hinkle and Edwin Olson. Predicting Object Functionality Using Physical Simulations. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2013.
* Ryan Morton and Edwin Olson. Robust Sensor Characterization via Max-Mixture Models: GPS Sensors. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2013.
* Robert Goeddel and Edwin Olson. Inferring Categories to Accelerate the Learning of New Classes. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2013.
* Andrew Richardson and Edwin Olson. Learning Convolutional Filters for Interest Point Detection. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) 2013.
* Johannes Strom and Edwin Olson. Multi-sensor ATTenuation Estimation (MATTE): Signal- strength prediction for teams of robots. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2012.
* Pratik Agarwal and Edwin Olson. Variable reordering strategies for SLAM. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2012.
* Robert Goeddel and Edwin Olson. DART: A Particle-based Method for Generating Easy-to-Follow Directions. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2012. CoTeSys Best Paper Finalist
* Edwin Olson and Yangming Li. IPJC: The Incremental Posterior Joint Compatibility Test for Fast Feature Cloud Matching. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2012.
* Pradeep Ranganathan and Edwin Olson. Gaussian Process for Lens Distortion Modeling. Pro- ceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2012.
* Edwin Olson and Pratik Agarwal. Inference on networks of mixtures for robust robot mapping. Proceedings of Robotics: Science and Systems (RSS) 2012.
* Jacob Crossman, Robert Marinier and Edwin Olson. A Hands-Off, Multi-Robot Display for Com- municating Situation Awareness to Operators. Proceedings of the International Conference on Collab- oration Technologies and Systems 2012.
* Andrew Richardson and Edwin Olson. Iterative Path Optimization for Practical Robot Planning. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2011.
* Johannes Strom and Edwin Olson. Occupancy Grid Rasterization in Large Environments for Teams of Robots. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2011.
* Ryan D. Morton and Edwin Olson. Positive and Negative Obstacle Detection using the HLD Classifier. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2011.
* Edwin Olson. AprilTag: A robust and flexible visual fiducial system. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) 2011.
* Edwin Olson. On computing the average orientation of vectors and lines. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) 2011.
* Yangming Li and Edwin Olson. Structure Tensors for General Purpose LIDAR Feature Extraction. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) 2011.
* Pradeep Ranganathan, Ryan Morton, Andrew Richardson, Johannes Strom, Robert Goeddel, Mi- hai Bulic and Edwin Olson. Coordinating a Team of Robots for Urban Reconnaisance. Proceedings of the Land Warfare Conference (LWC) 2010.
* Johannes Strom, Andrew Richardson and Edwin Olson. Graph-based Segmentation for Colored 3D Laser Point Clouds. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2010.
* Pradeep Ranganathan and Edwin Olson. Automated Safety Inspection of Grade Crossings. Pro- ceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2010.
* Edwin Olson. A Passive Solution to the Sensor Synchronization Problem. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2010.
* Albert Huang, Edwin Olson and David Moore. LCM: Lightweight Communications and Mar- shalling. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2010.
* Yangming Li and Edwin Olson. Extracting general-purpose features from LIDAR data. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) 2010.
* Edwin Olson. Real-Time Correlative Scan Matching. Proceedings of the IEEE International Con- ference on Robotics and Automation (ICRA) 2009.
* David C. Moore, Albert S. Huang, Matthew Walter, Edwin Olson, Luke Fletcher, John Leonard and Seth Teller. Simultaneous Local and Global State Estimation for Robotic Navigation. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) 2009.
* Albert Huang, David Moore, Matthew Antone, Edwin Olson and Seth Teller. Multi-Sensor Lane Finding in Urban Road Networks. Proceedings of Robotics: Science and Systems (RSS) 2008.
* Giorgio Grisetti, Dario Lodi Rizzini, Cyrill Stachniss, Edwin Olson and Wolfram Burgard. Online Constraint Network Optimization for Efficient Maximum Likelihood Map Learning. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) 2008.
* Edwin Olson, John Leonard and Seth Teller. Spatially-Adaptive Learning Rates for Online Incre- mental SLAM. Proceedings of Robotics: Science and Systems 2007.
* Edwin Olson, John Leonard and Seth Teller. Fast Iterative Alignment of Pose Graphs with Poor Initial Estimates. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) 2006. Google Scholar Classic Paper
* Edwin Olson, Matthew Walter, John Leonard and Seth Teller. Single Cluster Graph Partitioning for Robotics Applications. Proceedings of Robotics Science and Systems 2005.
* Edwin Olson, John Leonard and Seth Teller. Robust Range-Only Beacon Localization. IEEE Autonomous Underwater Vehicles (AUV ’04) 2004.
* Acshi Haggenmiller and Edwin Olson. Monte-Carlo Policy-Tree Decision Making. University of Michigan APRIL Laboratory 2022.
* Ryan J. Marcotte, Acshi Haggenmiller, Gonzalo Ferrer and Edwin Olson. Probabilistic Multi- Robot Search for an Adversarial Target. University of Michigan APRIL Laboratory 2019.
* Edwin Olson. AprilTag: A robust and flexible multi-purpose fiducial system. University of Michi- gan APRIL Laboratory 2010.
* Maximilian Krogius, Acshi Haggenmiller and Edwin Olson. Decentralized Multi-Policy Decision Making for Communication Constrained Multi-Robot Coordination (Preprint). Preprint 2021.
* Maximilian Krogius and Edwin Olson. Evolving Policy Sets for Multi-Policy Decision Making (Preprint). Preprint 2021.