Papers
11
Total Citations
118
H-Index
5
About
Rudi Penne is a researcher whose work spans robotics, computer vision, and intelligent systems, with particular expertise in robotic simulation, inspection path planning, and spatial sensing technologies. His most impactful contribution, the CoppeliaSim VR Toolbox (2020, 35 citations), bridges robot simulation software with virtual reality environments, enabling rapid prototyping and verification of robotic systems — a tool that has quickly gained traction in the robotics community. Penne has made significant strides in robotic inspection planning, developing gradient-based and near-optimal path optimization strategies that balance path efficiency with sensor coverage for complex objects. His work on RGB-D data processing for mobile robot self-localization demonstrates a consistent interest in robust, real-world sensing solutions across six degrees of freedom. Penne has also contributed to thermography measurement systems using industrial robots and time-of-flight imaging, reflecting his drive to push 3D sensing beyond conventional limits. With foundational contributions dating back to 1994 in mathematical methods of robotics, his career reflects both longevity and breadth. His research, published across venues including the Advanced Concepts for Intelligent Vision Systems conference, continues to shape how robots perceive, navigate, and interact with complex environments.
Research Focus
Key Achievements
Top Papers
- 1Connecting the CoppeliaSim robotics simulator to virtual reality35 citations · 2020
- 2Advanced Concepts for Intelligent Vision Systems24 citations · 2017
- 3A Gradient-Based Inspection Path Optimization Approach22 citations · 2018
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- 6Validation of an indoor ray launching RF propagation model3 citations · 2016
- 7Mathematical methods of robotics — editorial3 citations · 1994
- 8A Short Note on Point Singularities for Robot Manipulators3 citations · 2010
- 9A Simple Evaluation Procedure for Range Camera Measurement Quality3 citations · 2016
- 10Near-Optimal Path Planning for Complex Robotic Inspection Tasks3 citations · 2019