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Sherikov, Aleksander
Alternative names
Publications (2 of 2) Show all publications
Andreasson, H., Bouguerra, A., Cirillo, M., Dimitrov, D. N., Driankov, D., Karlsson, L., . . . Stoyanov, T. (2015). Autonomous transport vehicles: where we are and what is missing. IEEE robotics & automation magazine, 22(1), 64-75
Open this publication in new window or tab >>Autonomous transport vehicles: where we are and what is missing
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2015 (English)In: IEEE robotics & automation magazine, ISSN 1070-9932, E-ISSN 1558-223X, Vol. 22, no 1, p. 64-75Article in journal (Refereed) Published
Abstract [en]

In this article, we address the problem of realizing a complete efficient system for automated management of fleets of autonomous ground vehicles in industrial sites. We elicit from current industrial practice and the scientific state of the art the key challenges related to autonomous transport vehicles in industrial environments and relate them to enabling techniques in perception, task allocation, motion planning, coordination, collision prediction, and control. We propose a modular approach based on least commitment, which integrates all modules through a uniform constraint-based paradigm. We describe an instantiation of this system and present a summary of the results, showing evidence of increased flexibility at the control level to adapt to contingencies.

Keywords
Intelligent vehicles; Mobile robots; Resource management; Robot kinematics; Trajectory; Vehicle dynamics
National Category
Robotics
Identifiers
urn:nbn:se:oru:diva-44432 (URN)10.1109/MRA.2014.2381357 (DOI)000352030600010 ()2-s2.0-84925133099 (Scopus ID)
Available from: 2015-04-24 Created: 2015-04-24 Last updated: 2018-08-30Bibliographically approved
Dimitrov, D., Sherikov, A. & Wieber, P.-B. (2011). A sparse model predictive control formulation for walking motion generation. In: IEEE/RSJ International conference on Intelligent robots and systems (IROS): . Paper presented at IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS, 25-30 sept, 2011, San Francisco, CA (pp. 2292-2299). IEEE
Open this publication in new window or tab >>A sparse model predictive control formulation for walking motion generation
2011 (English)In: IEEE/RSJ International conference on Intelligent robots and systems (IROS), IEEE, 2011, p. 2292-2299Conference paper, Published paper (Refereed)
Abstract [en]

This article presents a comparison between dense and sparse model predictive control (MPC) formulations, in the context of walking motion generation for humanoid robots. The former formulation leads to smaller, the latter one to larger but more structured optimization problem. We put an accent on the sparse formulation and point out a number of advantages that it presents. In particular, motion generation with variable center of mass (CoM) height, as well as variable discretization of the preview window, come at a negligible additional computational cost. We present a sparse formulation that comprises a diagonal Hessian matrix and has only simple bounds (while still retaining the possibility to generate motions for an omnidirectional walk). Finally, we present the results from a customized code used to solve the underlying quadratic program (QP).

Place, publisher, year, edition, pages
IEEE, 2011
National Category
Robotics
Research subject
Computer Technology
Identifiers
urn:nbn:se:oru:diva-22892 (URN)10.1109/IROS.2011.6095035 (DOI)978-1-61284-454-1 (ISBN)
Conference
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS, 25-30 sept, 2011, San Francisco, CA
Available from: 2012-05-20 Created: 2012-05-20 Last updated: 2017-10-18Bibliographically approved

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