Ph.D. thesis

The thesis deals with comparing and analyzing sampling-based motion planning techniques, in particular variants of the Probabilistic Roadmap Method (PRM). In addition, quality aspects of paths and roadmaps are investigated.

Ph.D. thesis of Roland Geraerts.

• Roland Geraerts. Sampling-based Motion Planning: Analysis and Path Quality. Ph.D. thesis. Utrecht University. 2006.

  

  

Comparative studies and analyses

We conduct a comparative study of different techniques that are used in the Probabilistic Roadmap Method. In addition, we give a reachability analysis for sampling based planners which leads to a better understanding of the success of the planners.

Different sampling strategies and a 3D reachability region.

• Roland Geraerts and Mark H. Overmars. Reachability-based Analysis for Probabilistic Roadmap Planners. Robotics and Autonomous Systems (RAS), 55:824-836, 2007.

  

  

• Roland Geraerts and Mark H. Overmars. Reachability Analysis of Sampling Based Planners. In IEEE International Conference on Robotics and Automation (ICRA'05), pp. 406-412, 2005

  

  

• Roland Geraerts and Mark H. Overmars. Sampling and Node Adding in Probabilistic Roadmap Planners. Robotics and Autonomous Systems (RAS), 54:165-173, 2006.

  

  

• Roland Geraerts and Mark H. Overmars. Sampling Techniques for Probabilistic Roadmap Planners. In Conference on Intelligent Autonomous Systems (IAS-8), pp. 600-609, 2004.

  

  

• Roland Geraerts and Mark H. Overmars. A Comparative Study of Probabilistic Roadmap Planners. In Proc. Workshop on the Algorithmic Foundations of Robotics (WAFR'02), pp. 43-57, 2002.

  

  

High-quality paths

We present algorithms that increase the quality of a path. That is, we focus on decreasing the path length and increasing the clearance along a path. The techniques can be applied to a broad range of robots which may reside in arbitrary high-dimensional configuration spaces.

Techniques that improve the path clearance and path length.

• Roland Geraerts and Mark H. Overmars. Creating High-Quality Paths for Motion Planning. International Journal of Robotics Research (IJRR), 26:845-863, 2007.

  

  

• Roland Geraerts and Mark H. Overmars. On Improving the Clearance for Robots in High-Dimensional Configuration Spaces. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'05), pp. 4074-4079, 2005.

  

  

• Roland Geraerts and Mark H. Overmars. Clearance Based Path Optimization for Motion Planning. In IEEE International Conference on Robotics and Automation (ICRA'04), pp. 2386-2392, 2004.

  

  

High-quality roadmaps

The Reachability Roadmap Method is a new and efficient algorithm that creates small roadmaps for two- and three-dimensional problems. The algorithm ensures that a path can always be found if one exists. We extend the algorithm such that short paths and high-clearance paths can be extracted from the roadmap in real-time.

Techniques that improve the path clearance of a roadmap graph.

• Roland Geraerts and Mark H. Overmars. Creating High-quality Roadmaps for Motion Planning in Virtual Environments. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'06), pp. 4355-4361, 2006.

  

  

• Roland Geraerts and Mark H. Overmars. Creating Small Graphs for Solving Motion Planning Problems. In IEEE International Conference on Methods and Models in Automation and Robotics (MMAR'05) , pp. 531-536, 2005.

  

  

Experimental research

In robotics research, it is often difficult to compare and evaluate techniques experimentally. We identify these difficulties and provides solutions based on our work during the last four years in the field of sampling-based motion planning.

• Roland Geraerts. On Experimental Research in Sampling-based Motion Planning. In (IROS'06) Workshop on Benchmarks in Robotics Research , pp. 31-34, 2006.

  

  

Animation

We study techniques for combining path planning with motion synthesis.

Combining Path Planners and Motion Graphs

• Ben J.H. van Basten, Arjan Egges and Roland Geraerts. Combining Path Planners and Motion Graphs. Computer Animation and Virtual Worlds (CAVW), 22(1):59-78, 2011.

  

  

National ASCI/ICT.OPEN conferences

• Roland Geraerts and Mark H. Overmars. On the Analysis and Success of Sampling Based Motion Planning. In Conference of the Advanced School for Computing and Imaging (ASCI'05), pp. 313-319, 2005.

  

  

• On Improving the Path Quality for Motion Planning. In Conference of the Advanced School for Computing and Imaging (ASCI'04), pp. 211-217, 2004.

  

  

My papers on crowd simulation can be found here.