Editorial: Signal Processing Advances in Robots and Autonomy

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Linköping University Post Print

Editorial: Signal Processing Advances in

Robots and Autonomy

Frank Ehlers, Fredrik Gustafsson and Matthijs Spaan

N.B.: When citing this work, cite the original article.

Original Publication:

Frank Ehlers, Fredrik Gustafsson and Matthijs Spaan, Editorial: Signal Processing Advances

in Robots and Autonomy, 2009, EURASIP JOURNAL ON ADVANCES IN SIGNAL

PROCESSING, (2009), 948716.

http://dx.doi.org/10.1155/2009/948716

Copyright: Authors

Postprint available at: Linköping University Electronic Press

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Hindawi Publishing Corporation

EURASIP Journal on Advances in Signal Processing Volume 2009, Article ID 948716,3pages

doi:10.1155/2009/948716

Editorial

Signal Processing Advances in Robots and Autonomy

Frank Ehlers,

1

_{Fredrik Gustafsson (EURASIP Member),}

2

_{and Matthijs Spaan}

3 1_{NURC, NATO Research Centre, Viale S. Bartolomeo 400, 19126 La Spezia, Italy}

2_{Department of Electrical Engineering, Link¨oping University, 58183 Link¨oping, Sweden}

3_{Instituto de Sistemas e Rob´otica, Instituto Superior T´ecnico, Avenida Rovisco Pais 1, 1049-001 Lisboa, Portugal}

Correspondence should be addressed to Frank Ehlers,frankehlers@ieee.org Received 16 June 2009; Accepted 16 June 2009

Copyright © 2009 Frank Ehlers et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

The capabilities of robots and autonomous systems have increased dramatically over the past years. This success story partly depends on advances in signal processing which provide appropriate and eﬃcient analysis of sensor data and enable autonomy.

A key element of the transition of signal processing output to its exploitation inside robots and autonomous systems is the way uncertainty is managed: uncertainty originating from insuﬃcient sensor data, uncertainty about eﬀects of future autonomous actions, and, in the case of distributed sensors and actuators (like for a team of robots), uncertainty about communication lines.

The aim of this special issue is to focus on recent devel-opments that allow passing this transition path successfully, showing either where signal processing is used in robotics and autonomy or where robotics and autonomy had special demands that had not been fulfilled by signal processing before.

The articles in this special issue cover the following topics.

Autonomous Navigation

“Vector Field Driven Design for Lightweight Signal Process-ing and Control Schemes for Autonomous Robotic Naviga-tion,” “Vision-based Unmanned Aerial Vehicle Navigation Using Geo-referenced Information,” “Automatic evaluation of landmarks for image based navigation update,” and “Pure-Pursuit Reactive Path Tracking for Non-Holonomic Mobile Robots with a 2D Laser-Scanner.”

Robot Teams and Exploration

“Collaborative Area Monitoring Using Wireless Sensor Net-works with Stationary and Mobile Nodes,” and “A Common

Coordinates/Heading Direction Generation Method for a Robot Swarm with only RSSI-Based Ranging.”

Target Tracking Applications

“Self-Localisation and Stream Field Based Partially Observ-able Moving Object Tracking,” “A POMDP Framework for Coordinated Guidance of Autonomous UAVs for Multitarget Tracking,” and “Prioritized Multi-Hypothesis Tracking by a Mobile Robot.”

Autonomous Navigation

N. J. Mathai et al. address the problem of realizing light-weight signal processing and control architectures for agents in multirobot systems. They present the design of an analog-amenable signal processing scheme. They use control and dynamical systems theory both as a description language and as a synthesis toolset to rigorously develop the computational machinery; these mechanisms are mated with structural insights from behavior-based robotics to compose overall algorithmic architectures. Their perspective is that robotic behaviors consist of actions taken by an agent to cause its sensory perception of the environment to evolve in a desired manner. To provide an intuitive aid for designing these behavioral primitives they present a novel visual tool, inspired vector field design, that helps the designer exploit the dynamics of the environment. They present simulation results and animation videos to demonstrate the signal processing and control architecture in action.

G. Conte et al. investigate the possibility of augmenting an Unmanned Aerial Vehicle (UAV) navigation system with a passive video camera in order to cope with long-term GPS outages. Their paper proposes a vision based navi-gation architecture which combines inertial sensors, visual

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2 EURASIP Journal on Advances in Signal Processing

odometry, and registration of the on-board video to a geo-referenced aerial image. The vision-aided navigation system developed is capable of providing high-rate and drift-free state estimation for UAV autonomous navigation without the GPS system. Due to the use of image-to-map regis-tration for absolute position calculation, drift-free position performance depends on the structural characteristics of the terrain.

Experimental evaluation of the approach based on o ﬀ-line flight data is provided. In addition, the architecture proposed has been implemented onboard as an experimental UAV helicopter platform and tested during vision-based autonomous flights.

S. Lang et al. address the automatic evaluation of landmarks for image-based navigation updates.

The successful mission of an autonomous airborne system like an unmanned aerial vehicle strongly depends on its accurate navigation. While GPS is not always available and pose estimation based solely on Inertial Measurement Unit drifts, image-based navigation may become a cheap and robust additional pose measurement device. For the actual navigation update they use a landmark-based approach. They found that it is essential that the used landmarks are well chosen. Therefore, they introduce an approach for evaluating landmarks in terms of the matching distance, which is the maximum misplacement in the position of the landmark that can be corrected. They validate the evaluations with a 3D reconstruction system working on data captured from a helicopter.

J. Morales et al. investigate the application of the Pure-Pursuit path tracking method for reactive tracking of paths that are implicitly defined by perceived environmental features. Due to its simplicity and efficiency, the Pure-Pursuit path tracking method has been widely employed for planned navigation of non-holonomic ground vehicles. Goal points are obtained through an efficient interpretation of range data from an onboard 2D laser-scanner to follow persons, corridors and walls. Moreover, this formulation allows that a robotic mission can be composed of a combination of different types of path segments. They have successfully tested these techniques in an indoor environment.

Robot Teams and Exploration

T. Lambrou et al. address the task of collaborative area monitoring using wireless sensor networks with stationary and mobile nodes. Monitoring a large area with stationary sensor networks requires a very large number of nodes which with current technology implies a prohibitive cost. The motivation of their work is to develop an architecture where a set of mobile sensors will collaborate with the stationary sensors in order to reliably detect and locate an event. The main idea of this collaborative architecture is that the mobile sensors should sample the areas that are least covered (monitored) by the stationary sensors. Furthermore, when stationary sensors have a “suspicion” that an event may have occurred, they report it to a mobile sensor that can move closer to the suspected area and can confirm whether the event has occurred or not. An

important component of the proposed architecture is that the mobile nodes autonomously decide their path based on local information (their own beliefs and measurements as well as information collected from the stationary sensors in a neighborhood around them).

S. Hara et al. present a common coordinates/heading direction generation method for a robot swarm with only Received Signal Strength Indicator-based ranging. In the motion control of a microrobot swarm, a key issue is how to autonomously generate a set of common coordinates among all robots and to notify each robot of its heading direction in the generated common coordinates, without any special devices for estimating location and bearing. The authors propose a set of common coordinates and a heading direction generation method for a robot swarm with only Received Signal Strength Indicator (RSSI) measured through wireless communications. They explain the principle of the proposed method and show some computer simulation results on the location and direction estimation errors. Finally, experimental results demonstrate using a swarm composed of five robots with the IEEE 802.15.4 standard as its wireless communication tool.

Target Tracking Applications

K.-S. Tseng et al. present an algorithm for self-localization and stream field based partially observable moving object tracking. Self-localisation and object tracking are key tech-nologies for human-robot interactions. Most previous track-ing algorithms focus on how to correctly estimate the position, velocity, and acceleration of a moving object based on the prior state and sensor information. What has been rarely studied so far is how a robot can successfully track the partially observable moving object with laser range finders if there is no preanalysis of object trajectories. In this case, traditional tracking algorithms may lead to the divergent estimation. The authors introduce a novel laser range finder based partially observable moving object tracking and self-localization algorithm for interactive robot applications. Dissimilar to the previous work, they adopt a stream field-based motion model and combine it with the Rao-Blackwellised particle filter (RBPF) to predict the object goal directly. This algorithm can keep predicting the object position by inferring the interactive force between the object goal and environmental features when the moving object is unobservable. Experimental results show that the robot with the proposed algorithm can localize itself and track the frequently occluded object. Compared with the traditional Kalman filter and particle filter based algorithms, the pro-posed one significantly improves the tracking accuracy.

S. Miller et al. discuss the application of the theory of partially observable Markov decision processes (POMDPs) to the design of guidance algorithms for controlling the motion of unmanned aerial vehicles with onboard sensors to improve tracking of multiple ground targets. While POMDP problems are intractable to solve exactly, principled approximation methods can be devised based on the theory that characterizes optimal solutions. A new approximation method called nominal belief-state optimization (NBO),

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EURASIP Journal on Advances in Signal Processing 3

combined with other application-specific approximations and techniques within the POMDP framework, produces a practical design that coordinates the UAVs to achieve good long-term mean-squared-error tracking performance in the presence of occlusions and dynamic constraints. The flexibility of the design is demonstrated by extending the objective to reduce the probability of a track swap in ambiguous situations.

P. Rybskie et al. apply prioritized multihypothesis track-ing to state estimation tasks of a mobile robot.

To act intelligently in complex and dynamic environ-ments, mobile robots must estimate the position of objects by using information obtained from a wide variety of sources. The authors formally describe the problem of estimating the state of objects in the environment where the robot can only task its sensors to view on object at a time. They contribute an object tracking method that generates and maintains multiple hypotheses that consist of a probabilistic state estimate that is generated by the individual sources of information. These diﬀerent hypotheses can be spatially disjoint such that they cannot all be viewed/verified by robot’s sensors simultaneously. Thus, the robot must decide toward which hypothesis its sensors should be tasked by evaluating each hypothesis on its likelihood of containing the object. The rankings of these hypotheses are set by the expected uncertainty in the object’s motion/process model, as well as the uncertainties in the sources of information used to track their positions. A detailed description of the algorithm is given together with extensive empirical results in simulation as well as experiments on actual robots that demonstrate the eﬀectiveness of the approach taken.

Acknowledgment

The guest editors of this special issue are much indebted to their authors and reviewers, who put a tremendous amount of eﬀort and dedication to make this issue a reality.

Frank Ehlers Fredrik Gustafsson Matthijs Spaan

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International Journal of Microwave Science and Technology

Special Issue on

CMOS Application to Wireless Communications

Call for Papers

Recent advances in semiconductor process technologies have motivated the development of fully integrated CMOS circuits for wireless communications. Consequently, tremendous research eﬀorts have been directed to the design and imple-mentation of CMOS radio-frequency integrated circuits (RFICs). The objective of this special issue is to highlight the up-to-date progress in the field of CMOS RF devices and circuits.

The International Journal of Microwave Science and Technology invites authors to submit papers for the special issue on CMOS RF. Original papers previously unpublished and not currently under review by another journal are solicited for this special issue. Topics of interest include, but are not limited to:

• CMOS and BiCMOS RF device technologies • Small-signal circuits

• Large-signal circuits • Mixed-signal circuits

• Millimeter-wave integrated circuits • Signal generation circuits

• Frequency-conversion circuits • Wide-band integrated circuits • Cellular system IC’s and architecture • Emerging RF applications

• Modeling and CAD

Before submission, authors should carefully read over the journal’s Author Guidelines, which are located at http://

www.hindawi.com/journals/ijmst/guidelines.html.

Prospec-tive authors should submit an electronic copy of their complete manuscript through the journal Manuscript Track-ing System at http://mts.hindawi.com/, according to the following timetable:

Manuscript Due September 1, 2009 First Round of Reviews December 1, 2009 Publication Date March 1, 2010

Lead Guest Editor

Liang-Hung Lu, Department of Electrical Engineering,

National Taiwan University, Roosevelt Road, Taipei 106, Taiwan;lhlu@cc.ee.ntu.edu.tw

Guest Editor

Huei Wang, Department of Electrical Engineering,

National Taiwan University, Roosevelt Road, Taipei 106, Taiwan;hueiwang@ntu.edu.tw

Hindawi Publishing Corporation http://www.hindawi.com

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International Journal of Biomedical Imaging

Special Issue on

Mathematical Methods for Images and Surfaces

Call for Papers

“The Midwest Conference on Mathematical Methods for Images and Surfaces” was held in the Michigan State University on April 18-19. It created an excellent forum for researchers from engineering, biological, and mathematical sciences to exchange ideas and keep up with new develop-ments. To further disseminate research findings presented and exchanged in the conference, The International Journal

of Biomedical Imaging will publish a special issue entitled

“Mathematical Methods for Images and Surfaces.”

The scope of this special issue is the same as that of the conference. However, to better fit the scope of the journal, research findings relevant to biomedical science and technology are particularly welcome. Original papers and high-quality overviews on a wide range of topics in images and surfaces are solicited for this special issue. Topics of interest include, but are not limited to:

• Geometric flows, higher-order curvature flows, gradi-ent flows for image, and surface analysis

• Mumford-Shah functional

• Level set methods and their applications • Wavelets, frames, and multiresolution analysis • Mathematical algorithms for images and surfaces • Image edge detection, segmentation, pattern

recogni-tion, and video analysis and processing

• Computational methods for biomedical imaging • Algorithms for bioluminescence imaging, fluorescent

imaging, PET imaging, ultrasound imaging, MRI, and tomography

• Computational methods for anatomy

• Mathematical analysis of protein and membrane sur-faces

The papers solicited for this special issue are not restricted to the contributions presented during the Conference. Submissions from other researchers which fit the scope of this special issue are also welcome.

Before submission authors should carefully read over the journal’s Author Guidelines, which are located athttp://www .hindawi.com/journals/ijbi/guidelines.html. Prospective au-thors should submit an electronic copy of their complete

manuscript through the journal Manuscript Tracking Sys-tem at http://mts.hindawi.com/according to the following timetable:

Manuscript Due October 1, 2009 First Round of Reviews January 1, 2010 Publication Date April 1, 2010

Guowei Wei, Department of Mathematics and Department

of Electrical and Computer Engineering, Michigan State University, MI 48824, USA;wei@math.msu.edu

Guest Editors

Lalita Udpa, Department of Electrical and Computer

Engineering, Michigan State University, MI 48824, USA;

udpal@egr.msu.edu

Yang Wang, Chair of Department of Mathematics,

Michigan State University, MI 48824, USA;

ywang@math.msu.edu

Shan Zhao, Department of Mathematics, University of

Alabama, AL 35406, USA;szhao@bama.ua.edu

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International Journal of Digital Multimedia Broadcasting

Special Issue on

Multicell Cooperation and MIMO Technologies for

Broadcasting and Broadband Communications

Call for Papers

The wireless industry is experiencing an unprecedented increase in the number and sophistication of broadcasting and broadband communication systems. The growing dif-fusion of new services, like mobile television and multi-media communications, emphasizes the need of advanced transmission techniques that can fundamentally increase the system capacity. In this context, the multicell collaborative transmission is becoming one of a major subject of research in the wireless communication community as it has been identified as one of the underlying principles for future wire-less communication systems. Further, if perfect cooperation is assumed, it allows the entire network to be viewed as a single cell MIMO system with a distributed antenna array at the base station.

This special issue aims at promoting state-of-the-art research contributions from all research areas either directly involved in or contributing to improving the issues related to multicell cooperation and MIMO technologies for broad-casting and broadband communications. Topics of interest of this special issue include but are not limited to:

• Information theoretic aspects of cooperative commu-nication systems

• Cooperative broadcasting with uninformed transmit-ter

• Eﬀects of partial and incomplete channel state infor-mation in cooperative/MIMO systems

• Advances in MIMO and MISO algorithms and appli-cations

• Physical and MAC layer issues in cooperative/MIMO communications

• Performance analysis of distributed MIMO techniques • Space-time diversity technologies and space-time

cod-ing

• Practical implementations, test-beds, and demonstra-tions

• Standardization and deployment in 3G+, 4G, and beyond

Before submission authors should carefully read over the journal’s Author Guidelines, which are located athttp://www

.hindawi.com/journals/ijdmb/guidelines.html. Prospective

authors should submit an electronic copy of their complete manuscript through the journal Manuscript Tracking Sys-tem athttp://mts.hindawi.com/, according to the following timetable:

Manuscript Due September 1, 2009 First Round of Reviews December 1, 2009 Publication Date March 1, 2010

Hongxiang Li, Department of Electrical and Computer

Engineering, North Dakota State University, Fargo, ND 58103, USA;hongxiang.li@ndsu.edu

Guest Editors

Jinyun Zhang, Mitsubishi Electrical Research Labs

(MERL), Cambridge, MA 02139, USA;jzhang@merl.com

Lingjia Liu, Samsung Electronics, Richardson, TX 75082,

USA;lliu@sta.samsung.com

Guoqing Li, Intel Corporation, Hillsboro, OR 97124, USA;

guoqing.c.li@intel.com

Younsun Kim, Department of Electrical Engineering,

University of Washington, Seattle, WA 98195, USA;

younsun@u.washington.edu