Papers
17
Total Citations
187
H-Index
7
About
Thomas Emter is a robotics researcher whose career has been defined by advancing autonomous mobile robot navigation, with particular expertise in path planning, multi-sensor fusion, and localization for complex real-world environments. His most impactful contribution, "Application of Hybrid A* to an Autonomous Mobile Robot for Path Planning in Unstructured Outdoor Environments" (2022, 64 citations), demonstrates his ability to tackle the formidable challenge of navigating robots across mixed terrain encompassing both structured roads and unstructured regions. This work has become a key reference point in the field of autonomous outdoor navigation. Emter's research consistently addresses the full navigation pipeline. His investigations into multi-resolution lattice planning, dynamic environment obstacle avoidance, and multi-sensor fusion using GPS, IMUs, and Kinect sensors collectively reflect a systematic drive toward robust, deployable robotic systems. His work on disaster management robotics further highlights a commitment to socially meaningful applications, exploring how autonomous robots can assist rescue teams in hazardous scenarios. With contributions spanning algorithm toolboxes, SLAM techniques, stochastic sensor fusion, and modular agricultural field robots, Emter has built a broad and coherent body of work totaling over 160 citations, making him a noteworthy figure in applied autonomous systems research.
Research Focus
Key Achievements
Top Papers
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- 3Algorithm Toolbox for Autonomous Mobile Robotic Systems16 citations · 2017
- 4Situation responsive networking of mobile robots for disaster management15 citations · 2022
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- 8Modular and scalable automation for field robots7 citations · 2021
- 9Simultaneous Localization and Mapping with the Kinect sensor7 citations · 2012
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