Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Autonomous Robots
Published in: Autonomous Robots 1/2015

01-06-2015

A suboptimal and analytical solution to mobile robot trajectory generation amidst moving obstacles

Authors: Jun Peng, Wenhao Luo, Weirong Liu, Wentao Yu, Jing Wang

Published in: Autonomous Robots | Issue 1/2015

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

In this paper, we present a suboptimal and analytical solution to the trajectory generation of mobile robots operating in a dynamic environment with moving obstacles. The proposed solution explicitly addresses both the robot kinodynamic constraints and the geometric constraints due to obstacles while ensuring the suboptimal performance to a combined performance metric. In particular, the proposed design is based on a family of parameterized trajectories, which provides a unified way to embed the kinodynamic constraints, geometric constraints, and performance index into a set of parameterized constraint equations. To that end, the suboptimal solution to the constrained optimization problem can be analytically obtained. The solvability conditions to the constraint equations are explicitly established, and the proposed solution enhances the methodologies of real-time path planning for mobile robots with kinodynamic constraints. Both the simulation and experiment results verify the effectiveness of the proposed method.
next article Finger contact sensing and the application in dexterous hand manipulation

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now
Literature
Balkcom, D. J., & Mason, M. T. (2002). Time optimal trajectories for bounded velocity differential drive vehicles. The International Journal of Robotics Research (IJRR), 21, 199–217.CrossRef
Barraquand, J., & Latombe, J. C. (1991). Nonholonomic multibody mobile robots: Controllability and motion planning in the presence of obstacles. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 3, 2328–2335.
Bhattacharya, S., Likhachev, M., & Kumar, V. (2012). Topological constraints in search-based robot path planning. Autonomous Robots, 33(3), 273–290.CrossRef
Bicchi, A., Casalino, G., & Santilli, C. (1995). Planning shortest bounded-curvature paths for a class of nonholonomic vehicles among obstacles. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2, 1349–1354.
Bonnans, J.-F., et al. (2006). Numerical optimization: Theoretical and practical aspects. Heidelberg: Springer.
Borenstein, J., & Koren, Y. (1991). The vector field histogram-fast obstacle avoidance for mobile robots. IEEE Transactions on Robotics and Automation, 7, 278–288.CrossRef
Cheng, P., Frazzoli, E., & LaValle, S. (2008). Improving the performance of sampling-based motion planning with symmetry-based gap reduction. IEEE Transactions on Robotics, 24, 488–494.CrossRef
Divelbiss, A. W., & Wen, J. T. (1997). A path space approach to nonholonomic motion planning in the presence of obstacles. IEEE Transactions on Robotics and Automation, 13, 443–451.CrossRef
Dong, W., & Guo, Y. (2005). New trajectory generation methods for nonholonomic mobile robots. Proceedings of the international symposium on collaborative technologies and systems, pp. 353–358.
Duleba, I., & Sasiadek, J. Z. (2003). Nonholonomic motion planning based on Newton algorithm with energy optimization. IEEE Transactions on Control Systems Technology, 11, 355–363.CrossRef
Fiorini, P., & Shiller, Z. (1993). Motion planning in dynamic environments using the relative velocity paradigm. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 1, 560–565.CrossRef
Fliess, M., LeVine, J., Martin, P., & Rouchon, P. (1995). Flatness and defect of non-linear systems: Introductory theory and examples. International Journal of Control, 61, 1327–1361.CrossRefMATHMathSciNet
Guo, Y., & Tang, T. (2008). Optimal trajectory generation for nonholonomic robots in dynamic environments. Proceedings of the IEEE international conference on robotics and automation (ICRA), pp. 2552–2557.
Guo, Y., Li, Y., & Sheng, W. (2007). Global trajectory generation for nonholonomic robots in dynamic environments. Proceedings of the IEEE international conference on robotics and automation (ICRA), pp. 1324–1329.
Hashim, S., & Tien-Fu, L. (2009). A new strategy in dynamic time-dependent motion planning for nonholonomic mobile robots. IEEE international conference on robotics and biomimetics (ROBIO), pp. 1692–1697.
Howard, T. M., & Kelly, A. (2007). Optimal rough terrain trajectory generation for wheeled mobile robots. International Journal of Robotics Research (IJRR), 26(2), 141–166.CrossRef
John, S., et al. (2014). Motion planning with sequential convex optimization and convex collision checking. The International Journal of Robotics Research, 33(9), 1251–1270.CrossRef
Karaman, S., & Frazzoli, E. (2010). Optimal kinodynamic motion planning using incremental sampling-based methods. In: 49th IEEE conference on decision and control (CDC), pp. 7681–7687.
Kim, J. O., & Khosla, P. K. (1992). Real-time obstacle avoidance using harmonic potential functions. IEEE Transactions on Robotics and Automation, 8, 338–349.CrossRef
Kindel, R., Hsu, D., Latombe, J. C., & Rock, S. (2000). Kinodynamic motion planning amidst moving obstacles. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 1, 537–543.
Koenig, Sven, & Likhachev, Maxim. (2002). D* Lite. Proceedings of the eighteenth national conference on artificial intelligence (AAAI), pp. 476–483.
Kushleyev, A., & Likhachev, M. (2009). Time-bounded lattice for efficient planning in dynamic environments. Proceedings of the IEEE international conference on robotics and automation (ICRA), pp. 1662–1668.
Ladd, A. M., & Kavraki, L. E. (2004). Measure theoretic analysis of probabilistic path planning. IEEE Transactions on Robotics and Automation, 20, 229–242.CrossRef
LaValle, S. M., & Kuffner, J. J, Jr. (1999). Randomized kinodynamic planning. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 1, 473–479.
Li, Z. X., & Canny, J. (1992). Nonholonomic motion planning, Dordrecht. The Netherlands: Kluwer.
Likhachev, M., & Ferguson, D. (2009). Planning long dynamically-feasible maneuvers for autonomous vehicles. International Journal of Robotics Research (IJRR), 28(8), 933–945.CrossRef
Liu, S., & Sun, D. (2011). Optimal motion planning of a mobile robot with minimum energy consumption. IEEE/ASME international conference on advanced intelligent mechatronics (AIM), pp. 43–48.
De Luca, A., Oriolo, G., & Samson, C. (1998). Feedback control of a nonholonomic car-like robot. Robot Motion Planning and Control, 229, 171–253.CrossRef
Lvine, J. (2009). Analysis and control of nonlinear systems: A flatness-based approach. Berlin: Springer.CrossRef
Morales, J. L., Nocedal, J., Wu, Y. (2011). A sequential quadratic programming algorithm with an additional equality constrained phase. IMA Journal of Numerical Analysis, drq037.
Murray, R. M., & Sastry, S. S. (1993). Nonholonomic motion planning: Steering using sinusoids. IEEE Transactions on Automatic Control, 38, 700–716.CrossRefMATHMathSciNet
Narayanan, V., Phillips, M., & Likhachev, M. (2012). Anytime safe interval path planning for dynamic environments. Proceedings of the IEEE/RSJ international conference on intelligent robots and systems (IROS), pp. 4708–4715.
Pivtoraiko, M., Knepper, R. A., & Kelly, A. (2009). Differentially constrained mobile robot motion planning in state lattices. Journal of Field Robotics (JFR), 26(3), 308–333.CrossRef
Qu, Z., Wang, J., & Plaisted, C. E. (2004). A new analytical solution to mobile robot trajectory generation in the presence of moving obstacles. IEEE Transactions on Robotics, 20, 978–993.CrossRef
Reister, D. B., & Pin, F. G. (1994). Time-optimal trajectories for mobile robots with two independently driven wheels. The International Journal of Robotics Research (IJRR), 13, 38–54.CrossRef
Shiller, Z., Gal, O., & Raz, A. (2011). Adaptive time horizon for on-line avoidance in dynamic environments. Proceedings of the IEEE/RSJ international conference on intelligent robots and systems (IROS), pp. 3539–3544.
Shiller, Z., Large, F., & Sekhavat, S. (2001). Motion planning in dynamic environments: Obstacles moving along arbitrary trajectories. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 4, 3716–3721.
Tilbury, D., & Murray, R. M. (1995). Trajectory generation for the N-trailer problem using Goursat normal form. IEEE Transactions on Automatic Control, 40, 802–819.CrossRefMATHMathSciNet
Ucan, X. I., & Kavraki, L. E. (2012). A sampling-based tree planner for systems with complex dynamics. IEEE Transactions on Robotics, 28, 116–131.CrossRef
van den Berg, J., & Overmars, M. (2007). Kinodynamic motion planning on roadmaps in dynamic environments. Proceedings of the IEEE/RSJ international conference on intelligent robots and systems (IROS), pp. 4253–4258.
Wu, A., & How, J. P. (2012). Guaranteed infinite horizon avoidance of unpredictable, dynamically constrained obstacles. Autonomous Robots, 32(3), 227–242.CrossRefMathSciNet
Yang, J., Daoui, A., Qu, Z., Wang, J., & Hull, R. A. (2005). An optimal and real-time solution to parameterized mobile robot trajectories in the presence of moving obstacles. Proceedings of the IEEE international conference on robotics and automation (ICRA), pp. 4412–4417.
Yang, J., Qu, Z., Wang, J., & Conrad, K. (2010). Comparison of optimal solutions to real-time path planning for a mobile vehicle. IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans, 40, 721–731.CrossRef
Yuan, H., & Shim, T. (2011). Model based real-time collision-free motion planning for mobile robots in unknown dynamic environments. In: 14th international IEEE conference on intelligent transportation systems (ITSC), pp. 416–421.
Metadata
Title
A suboptimal and analytical solution to mobile robot trajectory generation amidst moving obstacles
Authors
Jun Peng
Wenhao Luo
Weirong Liu
Wentao Yu
Jing Wang
Publication date
01-06-2015
Publisher
Springer US
Published in
Autonomous Robots / Issue 1/2015
Print ISSN: 0929-5593
Electronic ISSN: 1573-7527
DOI
https://doi.org/10.1007/s10514-015-9424-5

Other articles of this Issue 1/2015

Autonomous Robots 1/2015 Go to the issue

OriginalPaper

Collision avoidance for aerial vehicles in multi-agent scenarios

OriginalPaper

Simultaneous people tracking and robot localization in dynamic social spaces

OriginalPaper

Finger contact sensing and the application in dexterous hand manipulation

OriginalPaper

An extendible reconfigurable robot based on hot melt adhesives

OriginalPaper

A hierarchical and adaptive mobile manipulator planner with base pose uncertainty