Speed Daemon: Experience-Based Mobile Robot Speed Scheduling

A time-optimal speed schedule results in a mobile robot driving along a planned path at or near the limits of the robot's capability. However, deriving models to predict the effect of increased speed can be very difficult. In this paper, we present a speed scheduler that uses previous experience, instead of complex models, to generate time-optimal speed schedules. The algorithm is designed for a vision-based, path-repeating mobile robot and uses experience to ensure reliable localization, low path-tracking errors, and realizable control inputs while maximizing the speed along the path. To our knowledge, this is the first speed scheduler to incorporate experience from previous path traversals in order to address system constraints. The proposed speed scheduler was tested in over 4 km of path traversals in outdoor terrain using a large Ackermann-steered robot travelling between 0.5 m/s and 2.0 m/s. The approach to speed scheduling is shown to generate fast speed schedules while remaining within the limits of the robot's capability.

[1]  A. Sim,et al.  MOBILE ROBOT TRAJECTORY PLANNING WITH DYNAMIC AND KINEMATIC CONSTRAINTS , 1994 .

[2]  Alonzo Kelly,et al.  Rough Terrain Autonomous Mobility—Part 2: An Active Vision, Predictive Control Approach , 1998, Auton. Robots.

[3]  Karl Iagnemma,et al.  Vibration-based terrain classification for planetary exploration rovers , 2005, IEEE Transactions on Robotics.

[4]  Reza Fotouhi,et al.  Trajectory and temporal planning of a wheeled mobile robot on an uneven surface , 2009, Robotica.

[5]  Corrado Guarino Lo Bianco.  Kinematically constrained smooth real-time velocity planning for robotics applications , 2009, 2009 IEEE International Conference on Control and Automation.

[6]  Sebastian Thrun,et al.  Stanley: The robot that won the DARPA Grand Challenge , 2006, J. Field Robotics.

[7]  Raffaello D'Andrea,et al.  Trajectory generation and control for four wheeled omnidirectional vehicles , 2006, Robotics Auton. Syst..

[8]  S. Zucker,et al.  Toward Efficient Trajectory Planning: The Path-Velocity Decomposition , 1986 .

[9]  Claude Samson,et al.  Feedback control of a nonholonomic wheeled cart in Cartesian space , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.

[10]  Antonio Simón Mata,et al.  Velocity, acceleration and deceleration bounds for a time-optimal planner of a wheeled mobile robot , 2002, Robotica.

[11]  Antonio Simón Mata,et al.  Optimal Velocity Planning of Wheeled Mobile Robots on Specific Paths in Static and Dynamic Environments , 2003, J. Field Robotics.

[12]  Peter N. Nikiforuk,et al.  Trajectory planning and speed control for a two-link rigid manipulator , 2002 .

[13]  Alonzo Kelly,et al.  Rough Terrain Autonomous Mobility—Part 1: A Theoretical Analysis of Requirements , 1998, Auton. Robots.

[14]  Timothy D. Barfoot,et al.  Visual teach and repeat for long-range rover autonomy , 2010 .

[15]  Kazuya Yoshida,et al.  Development of multi-D.O.F. tracked vehicle to traverse weak slope and climb up rough slope , 2013, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems.