A Virtual Reality Visualization Ofan Analytical Solution Tomobile Robot Trajectory Generationin The Presence Of Moving Obstacles

Virtual visualization of mobile robot analytical trajectories while avoiding moving obstacles is presented in this thesis as a very helpful technique to properly display and communicate simulation results. Analytical solutions to the path planning problem of mobile robots in the presence of obstacles and a dynamically changing environment have been presented in the current robotics and controls literature. These techniques have been demonstrated using twodimensional graphical representation of simulation results. In this thesis, the analytical solution published by Dr. Zhihua Qu in December 2004 is used and simulated using a virtual visualization tool called VRML.

[1]  G. Swaminathan.  Robot Motion Planning , 2006 .

[2]  Z. Qu,et al.  A new suboptimal control design for cascaded non‐linear systems , 2002 .

[3]  M. Fliess,et al.  Flatness and defect of non-linear systems: introductory theory and examples , 1995 .

[4]  Steven W. Zucker,et al.  Planning collision-free trajectories in time-varying environments: a two-level hierarchy , 2005, The Visual Computer.

[5]  Zhihua Qu,et al.  A new analytical solution to mobile robot trajectory generation in the presence of moving obstacles , 2004, IEEE Transactions on Robotics.

[6]  S. Sastry,et al.  Nonholonomic motion planning: steering using sinusoids , 1993, IEEE Trans. Autom. Control..

[7]  Vatana An.  A Third-order Differential Steering Robot And Trajectory Generation In The Presence Of Moving Obstacles , 2006 .

[8]  H. Sussmann,et al.  Limits of highly oscillatory controls and the approximation of general paths by admissible trajectories , 1991, [1991] Proceedings of the 30th IEEE Conference on Decision and Control.

[9]  Zvi Shiller,et al.  Motion planning in dynamic environments: obstacles moving along arbitrary trajectories , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[10]  Richard M. Murray,et al.  A motion planner for nonholonomic mobile robots , 1994, IEEE Trans. Robotics Autom..

[11]  S. Sastry,et al.  Trajectory generation for the N-trailer problem using Goursat normal form , 1993, Proceedings of 32nd IEEE Conference on Decision and Control.

[12]  Jean-Claude Latombe,et al.  Nonholonomic multibody mobile robots: Controllability and motion planning in the presence of obstacles , 2005, Algorithmica.

[13]  C. Fernandes,et al.  Near-optimal nonholonomic motion planning for a system of coupled rigid bodies , 1994, IEEE Trans. Autom. Control..

[14]  D. Normand-Cyrot,et al.  An introduction to motion planning under multirate digital control , 1992, [1992] Proceedings of the 31st IEEE Conference on Decision and Control.

[15]  Paolo Fiorini,et al.  Motion Planning in Dynamic Environments Using Velocity Obstacles , 1998, Int. J. Robotics Res..

[16]  Jean-Paul Laumond,et al.  Robot Motion Planning and Control , 1998 .

[17]  Steven M. LaValle,et al.  Randomized Kinodynamic Planning , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

[18]  John T. Wen,et al.  A path space approach to nonholonomic motion planning in the presence of obstacles , 1997, IEEE Trans. Robotics Autom..

[19]  Zvi Shiller,et al.  Optimal obstacle avoidance based on the Hamilton-Jacobi-Bellman equation , 1994, IEEE Trans. Robotics Autom..

[20]  J. Meditch,et al.  Applied optimal control , 1972, IEEE Transactions on Automatic Control.

[21]  Richard M. Murray,et al.  A Mathematical Introduction to Robotic Manipulation , 1994 .

[22]  L. Shepp,et al.  OPTIMAL PATHS FOR A CAR THAT GOES BOTH FORWARDS AND BACKWARDS , 1990 .

[23]  Yoram Koren,et al.  The vector field histogram-fast obstacle avoidance for mobile robots , 1991, IEEE Trans. Robotics Autom..

[24]  Jean-Claude Latombe,et al.  Randomized Kinodynamic Motion Planning with Moving Obstacles , 2002, Int. J. Robotics Res..

[25]  Tomás Lozano-Pérez,et al.  On multiple moving objects , 1986, Proceedings. 1986 IEEE International Conference on Robotics and Automation.

[26]  Daniel E. Koditschek,et al.  Exact robot navigation using artificial potential functions , 1992, IEEE Trans. Robotics Autom..

[27]  J. Sussmann,et al.  SHORTEST PATHS FOR THE REEDS-SHEPP CAR: A WORKED OUT EXAMPLE OF THE USE OF GEOMETRIC TECHNIQUES IN NONLINEAR OPTIMAL CONTROL. 1 , 1991 .