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Paper WeA06.6

Sprunk, Christoph (University of Freiburg), Lau, Boris (University of Freiburg), Burgard, Wolfram (University of Freiburg)

Improved Non-Linear Spline Fitting for Teaching Trajectories to Mobile Robots

Scheduled for presentation during the Regular Session "Trajectory Planning and Generation" (WeA06), Wednesday, May 16, 2012, 09:45−10:00, Meeting Room 6 (Oya'te)

2012 IEEE International Conference on Robotics and Automation, May 14-18, 2012, RiverCentre, Saint Paul, Minnesota, USA

This information is tentative and subject to change. Compiled on October 19, 2017

Keywords Intelligent Transportation Systems, Industrial Robots

Abstract

In this paper, we present improved spline fitting techniques with the application of trajectory teaching for mobile robots. Given a recorded reference trajectory, we apply non-linear least-squares optimization to accurately approximate the trajectory using a parametric spline. The fitting process is carried out without fixed correspondences between data points and points along the spline, which improves the fit especially in sharp curves. By using a specific path model, our approach requires substantially fewer free parameters than standard approaches to achieve similar residual errors. Thus, the generated paths are ideal for subsequent optimization to reduce the time of travel or for the combination with autonomous planning to evade obstacles blocking the path. Our experiments on real-world data demonstrate the advantages of our method in comparison with standard approaches.

 

 

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