Michael Otte
Associate Professor
Directs the Motion and Teaming Lab, developing motion planning and mission planning for heterogeneous robot swarms and multi-agent teams.
Michael Otte's lab at UMD works on planning, control & multi-robot systems and reasoning & neuro-symbolic AI. 13 papers since 2023, mostly Autonomous Robots and RA-L. 7 PhD students and 4 master's students. 56 alumni.
At a glance
- papers, 2023–2026
- 3/ year
- at T1 venues
- 0%
- PhD students
- 7
- MS students
- 4
- alumni listed
- 56
Papers by yearfrom the lab homepage, 2023–2026
- 0 papers2026 · T1 0 · collecting
- 2 papers2025 · T1 0
- 4 papers2024 · T1 0
- 7 papers2023 · T1 0
T1 venuesOtherVenues: Autonomous Robots, RA-L
Research focuspaper titles that use each topic's words
- Planning, control & multi-robot systems6 papers
- motion3 papers
- planning2 papers
- Reasoning & neuro-symbolic AI0 papers
- teams0 papers
Paper list
From the lab homepage.
20252 papers
- In IEEE Conference on Decision and Control (CDC). Rio de Janeiro, BrazilControl Barrier Functions via Minkowski Operations for Safe Navigation among Polytopic Sets
- Autonomous RobotsMulti-Robot Exploration for the CADRE Mission
20244 papers
- In AIAA Accelerating Space Commerce, Exploration, and New Discovery (ASCEND). Las Vegas, NevadaAssembly Sequence Optimization for Space Structures
- In International Conference on Autonomous Agents and Multiagent Systems (AAMAS). Extended abstract. Auckland, New ZealandEnhancing Search and Rescue Capabilities in Hazardous Communication-Denied Environments through Path-Based Sensors with Backtracking
- Otte. In AIAA Science and Technology Forum (SciTech). Orlando, USATrajectory Tracking while Stabilizing an Inverted Pendulum on a Quadcopter Using Adaptive Model-Predictive Control
- In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Abu Dhabi, UAEValuing Attrition in a Fleet of Robots Used as Path-Based Sensors for Gathering Information in a Communications Restricted Environment
20237 papers
- RA-LA Heuristic-Guided Dynamical Multi-Rover Motion Planning Framework for Planetary Surface Missions
- In American Control Conference (ACC). San Diego, USAClosed-Form Active Learning using Expected Variance Reduction of Gaussian Process Surrogates for Adaptive Sampling
- International Workshop on the Algorithmic Foundations of Robotics (WAFR). College Park, USA, . . . ♠ Also appeared as a chapter in the book: Algorithmic Foundations of Robotics XV, 98--114.Decentralized Robot Swarm Clustering: Adding Resilience to Malicious Masquerade Attacks
- In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Detroit, USAExploration-Exploitation Active Learning of Gaussian Process Surrogates for Adaptive Sampling
- In IEEE International Conference on Robotics and Automation (ICRA). London, UKLow-Level Controller in Response to Changes in Quadrotor Dynamics
- Jaffar and Michael Otte. International Workshop on the Algorithmic Foundations of Robotics (WAFR). College Park, USA, . . . ♠ Also appeared as a chapter in the book: Algorithmic Foundations of Robotics XV, 132--148.PiP-X: Funnel-based Online Feedback Motion Planning/Replanning in Dynamic Environments
- AIAA Journal of Aerospace Information Systems.Simultaneous Motion Replanning and Gravity Model Refinement Near Small Solar System Bodies
Where alumni went56 listed
Apply to UMDFall 2027
Not announced yet
UMD Computer Science PhD
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- Single round
- Opens
- —
- GRE
- See program page
- English
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- Fee
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Not yet confirmed for this intake.
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