A Sampling-Based Partial Motion Planning Framework for System-Compliant Navigation along a Reference Path

July 1, 2013 in ETHZ-ASL, Publications

Ulrich Schwesinger, Martin Rufli , Paul Furgale, and Roland Siegwart

IEEE Intelligent Vehicles Symposium (IVS) 2013

In this paper a generic framework for sampling-based partial motion planning along a reference path is presented. The sampling mechanism builds on the specification of a vehicle model and a control law, both of which are freely selectable. Via a closed-loop forward simulation, the vehicle model is regulated onto a carefully chosen set of terminal states aligned with the reference path, generating system-compliant sample trajectories in accordance with the specified system and environmental constraints. The consideration of arbitrary state and input limits make this framework appealing to nonholonomic systems. The rich trajectory set is evaluated in an online sampling-based planning framework, targeting real-time motion planning in dynamic environments.

In an example application, a Volkswagen Golf is modeled via a kinodynamic single-track system that is further constrained by steering angle/rate and velocity/acceleration limits. Control is implemented via state-feedback onto piecewise C0 -continuous reference paths. Experiments demonstrate the planner’s applicability to online operation, its ability to cope with discontinuous reference paths as well as its capability to navigate in a realistic traffic scenario.


@inproceedings{ schwesinger_iv13,
Address = {Gold Coast, Australia},
Author = {Schwesinger, Ulrich and Rufli, Martin and Furgale, Paul and Siegwart, Roland},
Booktitle = {IEEE Intelligent Vehicles Symposium (IV)},
Month = {23--26 June},
Pages = {391--396},
Title = {A Sampling-Based Partial Motion Planning Framework for System-Compliant Navigation along a Reference Path},
Year = {2013}
}

Article full text

Self-supervised Calibration for Robotic Systems

July 1, 2013 in ETHZ-ASL, Publications

Jérôme Maye, Paul Furgale, and Roland Siegwart

IEEE Intelligent Vehicles Symposium (IVS) 2013

We present a generic algorithm for self calibration of robotic systems that utilizes two key innovations. First, it uses information theoretic measures to automatically identify and store novel measurement sequences. This keeps the computation tractable by discarding redundant information and allows the system to build a sparse but complete calibration dataset from data collected at different times. Second, as the full observability of the calibration parameters may not be guaranteed for an arbitrary measurement sequence, the algorithm detects and locks unobservable directions in parameter space using a truncated QR decomposition of the Gauss-Newton system. The result is an algorithm that listens to an incoming sensor stream, builds a minimal set of data for estimating the calibration parameters, and updates parameters as they become observable, leaving the others locked at their initial guess. Through an extensive set of simulated and real-world experiments, we demonstrate that our method outperforms state-of-the-art algorithms in terms of stability, accuracy, and computational efficiency.


@inproceedings{maye_iv13,
Address = {Gold Coast, Australia},
Author = {Maye, Jerome and Furgale, Paul and Siegwart, Roland},
Booktitle = {IEEE Intelligent Vehicles Symposium (IV)},
Month = {23--26 June},
Pages = {473--480},
Title = {Self-supervised Calibration for Robotic Systems},
Year = {2013}
}

Article full text

Rolling Shutter Camera Calibration

July 1, 2013 in ETHZ-ASL, Publications

Luc Oth, Paul Furgale, Laurent Kneip, Roland Siegwart

2013 IEEE Conference on Computer Vision and Pattern Recognition

Rolling Shutter (RS) cameras are used across a wide range of consumer electronic devices—from smart-phones to high-end cameras. It is well known, that if a RS camera is used with a moving camera or scene, significant image distortions are introduced. The quality or even success of structure from motion on rolling shutter images requires the usual intrinsic parameters such as focal length and distortion coefficients as well as accurate modelling of the shutter timing.

The current state-of-the-art technique for calibrating the shutter timings requires specialised hardware. We present a new method that only requires video of a known calibration pattern. Experimental results on over 60 real datasets show that our method is more accurate than the current state of the art.


@inproceedings{oth_cvpr13,
Author = {Luc Oth and Paul Furgale and Laurent Kneip and Roland Siegwart},
Booktitle = {Computer Vision and Pattern Recognition (CVPR), 2013 IEEE Conference on},
Month = {25--27 June},
Title = {Rolling Shutter Camera Calibration},
Year = {2013}
}

Article full text

Toward Automated Driving in Cities using Close-to-Market Sensors, an Overview of the V-Charge Project

July 1, 2013 in Bosch, ETHZ-ASL, ETHZ-CVG, Oxford-MRG, Parma-Vislab, Publications, TUB, VW

Paul Furgale et al.

IEEE Intelligent Vehicles Symposium (IVS) 2013

Future requirements for drastic reduction of CO2 production and energy consumption will lead to significant changes in the way we see mobility in the years to come.

However, the automotive industry has identified significant barriers to the adoption of electric vehicles, including reduced driving range and greatly increased refueling times. Automated cars have the potential to reduce the environmental impact of driving, and increase the safety of motor vehicle travel. The current state-of-the-art in vehicle automation requires a suite of expensive sensors. While the cost of these sensors is decreasing, integrating them into electric cars will increase the price and represent another barrier to adoption.

The V-Charge Project, funded by the European Commission, seeks to address these problems simultaneously by developing an electric automated car, outfitted with close-to-market sensors, which is able to automate valet parking and recharging for integration into a future transportation system. The final goal is the demonstration of a fully operational system including automated navigation and parking.

This paper presents an overview of the V-Charge system, from the platform setup to the mapping, perception, and planning sub-systems.


@inproceedings{furgale_iv13,
Address = {Gold Coast, Australia},
Annote = {full-conf-pb},
Author = {Paul Furgale and Ulrich Schwesinger and Martin Rufli and Wojciech Derendarz and Hugo Grimmett and Peter M\"{u}hlfellner and Stefan Wonneberger and Julian Timpner Stephan Rottmann and Bo Li and Bastian Schmidt and Thien Nghia Nguyen and Elena Cardarelli and Stefano Cattani and Stefan Br\"{u}ning and Sven Horstmann and Martin Stellmacher and Holger Mielenz and Kevin K\"{o}ser and Markus Beermann and Christian H\"{a}ne and Lionel Heng and Gim Hee Lee and Friedrich Fraundorfer and Ren\'{e} Iser and Rudolph Triebel and Ingmar Posner and Paul Newman and Lars Wolf and Marc Pollefeys and Stefan Brosig and Jan Effertz and C\'edric Pradalier and Roland Siegwart},
Booktitle = {IEEE Intelligent Vehicles Symposium (IV)},
Month = {23--26 June},
Pages = {809--816},
Title = {{Toward Automated Driving in Cities using Close-to-Market Sensors, an Overview of the V-Charge Project}},
Year = {2013}
}

Article full text

Using Multi-Camera Systems in Robotics: Efficient Solutions to the NPnP Problem

March 15, 2013 in ETHZ-ASL, Publications, year 2

Laurent Kneip, Paul Timothy Furgale, Roland Siegwart

2013 IEEE International Conference on Robotics and Automation (ICRA)

This paper introduces two novel solutions to the generalized-camera exterior orientation problem, which has a vast number of potential applications in robotics: (i) a minimal solution requiring only three point correspondences, and (ii) gPnP, an efficient, non-iterative n-point solution with linear complexity in the number of points. Already existing minimal solutions require exhaustive algebraic derivations. In contrast, our novel minimal solution is solved in a straightforward manner using the Gro ̈bner basis method. Existing n-point solutions are mostly based on iterative optimization schemes. Our n-point solution is non-iterative and outperforms existing algorithms in terms of computational efficiency. Our results present an evaluation against state-of-the-art single-camera algorithms, and a comparison of different multi-camera setups. It demonstrates the superior noise resilience achieved when using multi-camera configurations, and the efficiency of our algorithms. As a further contribution, we illustrate a possible robotic use-case of our non-perspective orientation computation algorithms by presenting visual odometry results on real data with a non-overlapping multi-camera configuration, including a comparison to a loosely coupled alternative.


@inproceedings{kneip_icra13,
Address = {Karlsruhe, Germany},
Author = {Laurent Kneip and Paul Timothy Furgale and Roland Siegwart},
Booktitle = {Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), to appear.},
Month = {6-10 May},
Title = {Using Multi-Camera Systems in Robotics: Efficient Solutions to the NPnP Problem},
Year = {2013}
}

ICRA13_1065_FI.pdf