This content is not included in your SAE MOBILUS subscription, or you are not logged in.
A Dynamic Local Trajectory Planning and Tracking Method for UGV Based on Optimal Algorithm
ISSN: 0148-7191, e-ISSN: 2688-3627
Published April 2, 2019 by SAE International in United States
This content contains downloadable datasetsAnnotation ability available
UGV (Unmanned Ground Vehicle) is gaining increasing amounts of attention from both industry and academic communities in recent years. Local trajectory planning is one of the most important parts of designing a UGV. However, there has been little research into local trajectory planning and tracking, and current research has not considered the dynamic of the surrounding environment. Therefore, we propose a dynamic local trajectory planning and tracking method for UGV driving on the highway in this paper. The method proposed in this paper can make the UGV travel from the navigation starting point to the navigation end point without collision on both straight and curve road. The key technology for this method is trajectory planning, trajectory tracking and trajectory update signal generation. Trajectory planning algorithm calculates a reference trajectory satisfying the demands of safety, comfort and traffic efficiency. A trajectory tracking controller based on model predictive control is used to calculate the control inputs to make the UGV travel along the reference trajectory. The trajectory update signal is generated when needed (e.g. there has a risk of collision in the future), causing the trajectory planning algorithm to re-plan new trajectory. Finally, the proposed local trajectory planning method is evaluated through simulation.
CitationSun, Y., Zhan, Z., Fang, Y., Zheng, L. et al., "A Dynamic Local Trajectory Planning and Tracking Method for UGV Based on Optimal Algorithm," SAE Technical Paper 2019-01-0871, 2019, https://doi.org/10.4271/2019-01-0871.
Data Sets - Support Documents
|[Unnamed Dataset 1]|
|[Unnamed Dataset 2]|
|[Unnamed Dataset 3]|
|[Unnamed Dataset 4]|
|[Unnamed Dataset 5]|
|[Unnamed Dataset 6]|
- Chang, S. and Gordon, T., “A Flexible Hierarchical Model-Based Control Methodology for Vehicle Active Safety Systems,” Vehicle System Dynamics 46(Supp. 1):63-75, 2008.
- Huang, C. and Fei, J., “Uav Path Planning Based on Particle Swarm Optimization with Global Best Path Competition,” International Journal of Pattern Recognition & Artificial Intelligence 32(1), 2017.
- Roberge, V., Tarbouchi, M., and Labonte, G., “Comparison of Parallel Genetic Algorithm and Particle Swarm Optimization for Real-Time Uav Path Planning,” IEEE Transactions on Industrial Informatics 9(1):132-141, 2013.
- Chen, Y.B., Luo, G.C., Mei, Y.S., Yu, J.Q. et al., “Uav Path Planning Using Artificial Potential Field Method Updated by Optimal Control Theory,” International Journal of Systems Science 47(6):1407-1420, 2016.
- Lynch, K.M., Shiroma, N., Arai, H., and Tanie, K., “Collision-Free Trajectory Planning for a 3-Dof Robot with a Passive Joint,” International Journal of Robotics Research 19(12):1171-1184, 2016.
- Pfeiffer, F., and Johanni, R. A Concept for Manipulator Trajectory Planning. in IEEE International Conference on Robotics and Automation. Proceedings (Vol. RA-3, 1399-1405). (1987).
- Jarvis, R.A., “Collision Free Trajectory Planning Using Distance Transforms,” Mech Eng Trans of the Ie Aust., 1985.
- Kant, K. and Zucker, S.W., “Toward Efficient Trajectory Planning: The Path-Velocity Decomposition,” International Journal of Robotics Research 5(3):72-89, 1986.
- Nilsson, N.J., “A Mobius Automation: An Application of Artificial Intelligence Techniques, in International Joint Conference on Artificial Intelligence, 1969, Morgan Kaufmann Publishers Inc., 509-520.
- Kavraki, L. E., Kolountzakis, M. N., and Latombe, J. C. Analysis of Probabilistic Roadmaps for Path Planning. in IEEE International Conference on Robotics and Automation, 1996. Proceedings (4, 3020-3025 (1996).
- Karaman, S. and Frazzoli, E., Sampling-Based Algorithms for Optimal Motion Planning (Sage Publications, Inc., 2011).
- Lavalle, S.M. and Kuffner, J.J., “Randomized Kinodynamic Planning,” IEEE International Conference on Robotics and Automation 1:473-479, 2002.
- Paden, B., Čáp, M., Yong, S.Z., Yershov, D. et al., “A Survey of Motion Planning and Control Techniques for Self-Driving Urban Vehicles,” IEEE Transactions on Intelligent Vehicles 1(1):33-55, 2016.
- Luo, Y., Xiang, Y., Cao, K., and Li, K., “A Dynamic Automated Lane Change Maneuver Based on Vehicle-to-Vehicle Communication,” Transportation Research Part C 62:87-102, 2016.
- Ji, J., Khajepour, A., Melek, W.W., and Huang, Y., “Path Planning and Tracking for Vehicle Collision Avoidance Based on Model Predictive Control with Multiconstraints,” IEEE Transactions on Vehicular Technology 66(2):952-964, 2017.
- Khatib, “Real-Time Obstacle Avoidance for Manipulators and Mobile Robots,” IEEE International Conference on Robotics and Automation. Proceedings 2:90-98, 2003.
- Li, X., Sun, Z., Cao, D., Liu, D., and He, H., “Development of a New Integrated Local Trajectory Planning and Tracking Control Framework for Autonomous Ground Vehicles,” Mechanical Systems & Signal Processing 87:118-137, 2017.
- Wang, L., Zhao, X., Su, H., and Tang, G., “Lane Changing Trajectory Planning and Tracking Control for Intelligent Vehicle on Curved Road,” Springerplus 5(1):1150, 2016.
- Lunhui, X.U., Luo, Q., Jianwei, W.U., and Huang, Y., “Study of Car-Following Model Based on Minimum Safety Distance,” Journal of Highway & Transportation Research & Development 6(1):72-78, 2010.
- Huang, Q. and Wang, H., “Fundamental Study of Jerk: Evaluation of Shift Quality and Ride Comfort,” SAE Technical Paper 2004-01-2065, 2004, doi:10.4271/2004-01-2065.
- Luca, A.D., Oriolo, G., and Samson, C., Feedback Control of a Nonholonomic Car-like Robot. Robot Motion Planning and Control (Berlin Heidelberg: Springer, 1998).
- UMTRI, “Safety Pilot Model Deployment.” [Online] Available: http://safetypilot.umtri.umich.edu/, accessed Aug. 31, 2018.
- Stein, C.M., “Estimation of the Mean of a Multivariate Normal Distribution,” Annals of Statistics 9(6):1135-1151, 1981.
- Kankar, P.K., Sharma, S.C., and Harsha, S.P., “Fault Diagnosis of Ball Bearings Using Continuous Wavelet Transform,” Applied Soft Computing Journal 11(2):2300-2312, 2011.