Hostname: page-component-78c5997874-v9fdk Total loading time: 0 Render date: 2024-11-13T09:27:26.841Z Has data issue: false hasContentIssue false
  • English
  • Français

Navigation of Semi-autonomous Service Robots Using Local Information and Anytime Motion Planners

Published online by Cambridge University Press:  14 January 2020

Guilherme A. S. Pereira Open the ORCID record for Guilherme A. S. Pereira [Opens in a new window]  and
Elias J. R. Freitas
Guilherme A. S. Pereira*
Affiliation:
Department of Mechanical and Aerospace Engineering, West Virginia University, 1374 Evansdale Drive, Morgantown, WV 26506-6070, USA
Elias J. R. Freitas
Affiliation:
Federal Institute of Minas Gerais, Rua Jose Benedito 369, Santa Efigenia, Itabirito, MG 35450-000, Brazil
*
*Corresponding author. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Summary

This paper deals with the problem of navigating semi-autonomous mobile robots without global localization systems in unknown environments. We propose a planning-based obstacle avoidance strategy that relies on local maps and a series of short-time coordinate frames. With this approach, simple odometry and range information are sufficient to make the robot to safely follow the user commands. Different from reactive obstacle avoidance strategies, the proposed approach chooses a good and smooth local path for the robot. The methodology is evaluated using a mobile service robot moving in an unknown corridor environment populated with obstacles and people.

Keywords

Service robotsNavigationObstacle avoidanceProbabilistic planners
Type
Articles
Information
Robotica , Volume 38 , Issue 11 , November 2020 , pp. 2080 - 2098
Copyright
Copyright © Cambridge University Press 2020

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Dayoub, F., Morris, T. and Corke, P., “Rubbing shoulders with mobile service robots,” IEEE Access 3, 333–342 (2015).CrossRefGoogle Scholar
Simpson, R. C., LoPresti, E. F. and Cooper, R. A., “How many people would benefit from a smart wheelchair?” J. Rehabil. Res. Dev. 45(1), 53 (2008).CrossRefGoogle ScholarPubMed
Müller, J., Stachniss, C., Arras, K. O. and Burgard, W., “Socially Inspired Motion Planning for Mobile Robots in Populated Environments,” Proceedings of the International Conference on Cognitive Systems (Springer, 2008) pp. 85–90.Google Scholar
Skog, I. and Handel, P., “In-car positioning and navigation technologies—a survey,” IEEE Trans. Intell. Transp. Syst. 10(1), 4–21 (2009).CrossRefGoogle Scholar
Andresen, F., Davis, L., Eastman, R. and Kambhampati, S., “Visual Algorithms for Autonomous Navigation,” Proceedings of the IEEE International Conference on Robotics and Automation, vol. 2 (IEEE, 1985) pp. 856–861.Google Scholar
Keirsey, D., Koch, E., McKisson, J., Meystel, A. and Mitchell, J., “Algorithm of Navigation for a Mobile Robot,” Proceedings of the IEEE International Conference on Robotics and Automation, vol. 1 (IEEE, 1984) pp. 574–583.Google Scholar
Khatib, O., “Real-time obstacle avoidance for manipulators and mobile robots,” Int. J. Robot. Res. 5(1), 90–98 (1986).CrossRefGoogle Scholar
Moravec, H. P., “Obstacle Avoidance and Navigation in the Real World by a Seeing Robot Rover,” Technical Report, DTIC Document (1980).Google Scholar
Arkin, R. C., Behavior-Based Robotics (MIT Press, Cambridge, 1998).Google Scholar
Balch, T., “Avoiding the Past: A Simple but Effective Strategy for Reactive Navigation,” Proceedings of the IEEE International Conference on Robotics and Automation (IEEE, 1993), pp. 678–685.CrossRefGoogle Scholar
Baklouti, E., Amor, N. B. and Jallouli, M., “Reactive control architecture for mobile robot autonomous navigation,” Robot. Auto. Syst. 89, 9–14 (2017).CrossRefGoogle Scholar
Chien, J.-C., Dang, Z.-Y. and Lee, J.-D., “Navigating a service robot for indoor complex environments,” Appl. Sci. 9(3), 491 (2019).CrossRefGoogle Scholar
Chik, S. F., Yeong, C. F., Su, E. L. M., Lim, T. Y., Subramaniam, Y. and Chin, P. J. H., “A review of social-aware navigation frameworks for service robot in dynamic human environments,” J. Telecommun. Electr. Comput. Eng. 8(11), 41–50 (2016).Google Scholar
Graf, B., “Reactive Navigation of an Intelligent Robotic Walking Aid,” Proceedings 10th IEEE International Workshop on Robot and Human Interactive Communication. ROMAN IEEE, 2001 (Cat. No. 01TH8591) (2001) pp. 353–358.Google Scholar
Pires, G. and Nunes, U., “A wheelchair steered through voice commands and assisted by a reactive fuzzy-logic controller,” J. Intell. Robot. Syst. 34(3), 301–314 (2002).CrossRefGoogle Scholar
Yang, H., Lim, J. and Yoon, S.-E., “Anytime RRBT for Handling Uncertainty and Dynamic Objects,” 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE, 2016) pp. 4786–4793.CrossRefGoogle Scholar
Pereira, G. A. S., Pimenta, L. C. A., Fonseca, A. R., Corrêa, L. D. Q., Mesquita, R. C., Chaimowicz, L., De Almeida, D. S. C. and Campos, M. F. M., “Robot navigation in multi-terrain outdoor environments,” Int. J. Robot. Res. 28(6), 685–700 (2009).CrossRefGoogle Scholar
Juliá, M., Gil, A. and Reinoso, O., “A comparison of path planning strategies for autonomous exploration and mapping of unknown environments,” Auto. Robot. 33(4), 427–444 (2012).CrossRefGoogle Scholar
Tian, F., Ge, S.-R. and Zhu, H., “A Navigation Control Strategy with Hybrid Architecture for Rescue Robot,” 2010 IEEE International Conference on Intelligent Computing and Intelligent Systems, vol. 1 (IEEE, 2010) pp. 675–680.CrossRefGoogle Scholar
Pereira, G. A. S., Choudhury, S. and Scherer, S., “A Framework for Optimal Repairing of Vector Field-Based Motion Plans,” Proceedings of the International Conference on Unmanned Aerial Systems (IEEE, 2016) pp. 261–266.Google Scholar
Karaman, S. and Frazzoli, E., “Sampling-based algorithms for optimal motion planning,” Int. J. Robot. Res. 30(7), 846–894 (2011).CrossRefGoogle Scholar
Minguez, J., Lamiraux, F. and Laumond, J.-P., “Motion planning and obstacle avoidance,” In: Siciliano, B., Khatib, O. (eds) Springer Handbook of Robotics (Springer, Berlin, Heidelberg, 2008) pp. 827–852.CrossRefGoogle Scholar
Karaman, S., Walter, M. R., Perez, A., Frazzoli, E. and Teller, S., “Anytime Motion Planning Using the RRT*,” Proceedings of the IEEE International Conference on Robotics and Automation (IEEE, 2011) pp. 1478–1483.Google Scholar
Fraichard, T., “A Short Paper About Motion Safety,” Proceedings 2007 IEEE International Conference on Robotics and Automation (IEEE, 2007) pp. 1140–1145.CrossRefGoogle Scholar
Gonçalves, V. M., Pimenta, L. C. A., Maia, C. A., Dutra, B. C. O. and Pereira, G. A. S., “Vector fields for robot navigation along time-varying curves in n-dimensions,” IEEE Trans. Robot. 26(4), 647–659 (2010).CrossRefGoogle Scholar
Ko, I., Kim, B. and Park, F. C., “Randomized path planning on vector fields,” Int. J. Robot. Res. 33(13), 1664–1682 (2014).CrossRefGoogle Scholar
Pereira, G. A. S., Choudhury, S. and Scherer, S., “Kinodynamic Motion Planning on Vector Fields Using RRT*,” Technical Report CMU-RI-TR-16-35 (Robotics Institute, Pittsburgh, PA, 2016).Google Scholar
Şucan, I. A., Moll, M. and Kavraki, L. E., “The open motion planning library,” IEEE Robot. Autom. Mag. 19(4), 72–82 (2012). http://ompl.kavrakilab.org.CrossRefGoogle Scholar
Quigley, M., Conley, K., Gerkey, B. P., Faust, J., Foote, T., Leibs, J., Wheeler, R. and Ng, A. Y., “ROS: An Open-Source Robot Operating System,” ICRA Workshop on Open Source Software (2009).Google Scholar
d’Andréa Novel, B., Campion, G. and Bastin, G., “Control of nonholonomic wheeled mobile robots by state feedback linearization,” Int. J. Robot. Res. 14(6), 543–559 (1995).CrossRefGoogle Scholar
Choset, H., Lynch, K. M., Hutchinson, S., Kantor, G. A., Burgard, W., Kavraki, L. E. and Thrun, S., Principles of Robot Motion: Theory, Algorithms, and Implementations, Intelligent Robotics and Autonomous Agents Series (MIT Press, Cambridge, 2005).Google Scholar
Kohlbrecher, S., Meyer, J., von Stryk, O. and Klingauf, U., “A Flexible and Scalable Slam System with Full 3d Motion Estimation,” Proceedings of IEEE International Symposium on Safety, Security and Rescue Robotics (SSRR) (IEEE, 2011).Google Scholar
Sheridan, T. B., “Human–robot interaction: Status and challenges,” Human Factors 58(4), 525–532 (2016).CrossRefGoogle ScholarPubMed