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Estimation of neighbor velocity in a leader-follower network
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.ORCID iD: 0000-0003-0177-1993
(English)Manuscript (preprint) (Other (popular science, discussion, etc.))
Abstract [en]

In applications where mobile robots are set to follow other moving objects, it is often assumed that not only the relative position, but also the velocity of the object in question is available to the tracking robots. In this paper, we consider a leader-follower system where the followers are equipped only with vision and range sensors. Thus, the followers can detect the positions of their neighbors, but they are unable both to measure the velocity of other agents directly and to obtain estimates of the unknown velocities through communication with other agents. In order to implement the desired leader-follower controls, the followers must use available sensor data to compute individual estimates of their respective leaders' velocities. One option would be to use the Extended Kalman Filter to obtain the estimates, but in this paper we take another approach and propose two separate state observers that can be used by the followers to obtain estimates of the missing velocities and that are also shown to stabilize the tracking controls used by the robots. To evaluate the observers, the tracking performance is compared in simulations for a system that uses observer estimates of the leader's velocity in the control equations and a system that computes the velocity estimates using the standard Extended Kalman Filter algorithm.

National Category
Computational Mathematics
URN: urn:nbn:se:kth:diva-10907OAI: diva2:231581
QC 20100715Available from: 2009-08-14 Created: 2009-08-14 Last updated: 2010-07-15Bibliographically approved
In thesis
1. Control and coordination of mobile multi-agent systems
Open this publication in new window or tab >>Control and coordination of mobile multi-agent systems
2009 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

In this thesis, various control problems originating from the field of mobile robotics are considered. In particular, the thesis deals with problems that are related to the interaction and coordination of multiple mobile units. The scientific contributions are presented in five papers that together constitute the main part of the thesis. The papers are preceded by a longer introductory part, in which some important results from control theory, data processing and robotics are reviewed.

In the first of the appended papers, two stabilizing tracking controls are proposed for a non-holonomic robot platform of unicycle type. Tolerance to errors and other properties of the controllers are discussed and a reactive obstacle avoidance control, that can easily be incorporated with the proposed tracking controls, is suggested. In Paper B, the results from Paper~A are extended to multi-agent systems. It is demonstrated how the tracking controls from Paper A can be used as building blocks when putting together formations of robots, in which each robot maintains a fixed position relative its neighbors during translation. In addition, switching between the different control functions is shown to be robust, implying that it is possible to change the shape of a formation on-line.

In the first two papers, the tracking problem is facilitated by the assumption that the approximate velocity of the target/leader is known to the tracking robot. Paper C treats the the case where the target velocity is neither directly measurable with the available sensor setup, nor possible to obtain through communication with neighboring agents. Straight-forward computation of the target velocity from available sensor data unfortunately tend to enhance measurement errors and give unreliable estimates. To overcome the difficulties, an alternative approach to velocity estimation is proposed, motivated by the local observability of the given control system.

Paper D deals with another problematic aspect of data acquisition. When using range sensors, one often obtains a mixed data set with measurements originating from many different sources. This problem would, for instance, be encountered by a robot moving in a formation, where it was surrounded by other agents. There exist established techniques for sorting mixed data sets off-line, but for time-depending systems where data need to be sorted on-line and only small time delays can be tolerated, established methods fail. The solution presented in the paper is a prediction-correction type algorithm, referred to as CCIA (Classification Correction and Identification algorithm).

Finally, in Paper E, we consider the problem of maintaining connectivity in a multi-agent system. Often inter-agent communication abilities are associated with some proximity constraints, so when the robots move in relation to each other, communication links both break and form. In the paper we present a framework for analysis that makes it possible to compute a set of general constraints which, if satisfied, are sufficient to guarantee maintained communication for a given multi-agent system. Constraints are computed for two sorts of consensus-based systems and the results are verified in simulations.

Place, publisher, year, edition, pages
Stockholm: KTH, 2009. x, 60 p.
Trita-MAT. OS, ISSN 1401-2294 ; 09:05
Mobile robotics, tracking, obstacle avoidance, formation control, nonlinear observers, multi-agent coordination, connectivity graphs.
National Category
Computational Mathematics
urn:nbn:se:kth:diva-10910 (URN)978-91-7415-396-5 (ISBN)
Public defence
2009-09-05, F3, Lindstedtsvägen 26, KTH, Stockholm, 10:00 (English)
QC 20100715Available from: 2009-08-26 Created: 2009-08-14 Last updated: 2010-07-15Bibliographically approved

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