Online Trajectory Generation: Basic Concepts for Instantaneous Reactions to Unforeseen Events

This paper introduces a new method for motion-trajectory generation of mechanical systems with multiple degrees of freedom (DOFs). The key feature of this new concept is that motion trajectories are generated online, i.e., within every control cycle, typically every millisecond. This enables systems to react instantaneously to unforeseen and unpredictable (sensor) events at any time instant and in any state of motion. As a consequence, (multi)sensor integration in robotics, in particular the development of control systems enabling sensor-guided and sensor-guarded motions, becomes greatly simplified. We introduce a class of online trajectory-generation algorithms and present the mathematical basics of this new approach. The algorithms presented here consist of three steps: calculation of the minimum synchronization time for all DOFs, synchronization of all DOFs, and calculation of output values. The theory is followed by real-world experimental results indicating new possibilities in robot-motion control.

[1]  George W. Irwin,et al.  A Practical Approach to Near Time-Optimal Inspection-Task-Sequence Planning for Two Cooperative Industrial Robot Arms , 1998, Int. J. Robotics Res..

[2]  Bruno Siciliano,et al.  Reactive collision avoidance for safer human-robot interaction , 2007 .

[3]  Wan Kyun Chung,et al.  Arbitrary states polynomial-like trajectory (ASPOT) generation , 2004, 30th Annual Conference of IEEE Industrial Electronics Society, 2004. IECON 2004.

[4]  Jean-Claude Latombe,et al.  Motion Planning: Recent Developments , 2018, Autonomous Mobile Robots.

[5]  Kostas J. Kyriakopoulos,et al.  Minimum jerk path generation , 1988, Proceedings. 1988 IEEE International Conference on Robotics and Automation.

[6]  Bernard Roth,et al.  The Near-Minimum-Time Control Of Open-Loop Articulated Kinematic Chains , 1971 .

[7]  R. F. King,et al.  An improved pegasus method for root finding , 1973 .

[8]  J. Bobrow,et al.  Time-Optimal Control of Robotic Manipulators Along Specified Paths , 1985 .

[9]  Sven Molkenstruck,et al.  A manipulator plays Jenga , 2008, IEEE Robotics & Automation Magazine.

[10]  Alessandro De Luca,et al.  Collision detection and reaction: A contribution to safe physical Human-Robot Interaction , 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[11]  Bruno Siciliano,et al.  Robot Force Control , 2000 .

[12]  S. Liu,et al.  An on-line reference-trajectory generator for smooth motion of impulse-controlled industrial manipulators , 2002, 7th International Workshop on Advanced Motion Control. Proceedings (Cat. No.02TH8623).

[13]  Friedrich M. Wahl,et al.  Towards On-Line Trajectory Computation , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[14]  Elizabeth A. Croft,et al.  Jerk-bounded manipulator trajectory planning: design for real-time applications , 2003, IEEE Trans. Robotics Autom..

[15]  Richard P. Paul,et al.  An On-Line Dynamic Trajectory Generator , 1984 .

[16]  Helge J. Ritter,et al.  On-line planning of time-optimal, jerk-limited trajectories , 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[17]  G. Hirzinger,et al.  The skeleton algorithm for self-collision avoidance of a humanoid manipulator , 2007, 2007 IEEE/ASME international conference on advanced intelligent mechatronics.

[18]  Frank Uhlig,et al.  Numerical Algorithms with C , 1996 .

[19]  Alexander Zelinsky,et al.  Quantitative Safety Guarantees for Physical Human-Robot Interaction , 2003, Int. J. Robotics Res..

[20]  Åke Björck,et al.  A new high order method of regula falsi type for computing a root of an equation , 1973 .

[21]  Alin Albu-Schäffer,et al.  A Unified Passivity-based Control Framework for Position, Torque and Impedance Control of Flexible Joint Robots , 2007, Int. J. Robotics Res..

[22]  François Chaumette,et al.  Visual Servoing and Visual Tracking , 2008, Springer Handbook of Robotics.

[23]  Steven M. LaValle,et al.  Current Issues in Sampling-Based Motion Planning , 2005, ISRR.

[24]  M. Steinbuch,et al.  Trajectory planning and feedforward design for high performance motion systems , 2004, Proceedings of the 2004 American Control Conference.

[25]  Jing Xiao,et al.  Real-Time Adaptive Motion Planning (RAMP) of Mobile Manipulators in Dynamic Environments With Unforeseen Changes , 2008, IEEE Transactions on Robotics.

[26]  Oliver Brock,et al.  Elastic Roadmaps: Globally Task-Consistent Motion for Autonomous Mobile Manipulation in Dynamic Environments , 2006, Robotics: Science and Systems.

[27]  O. Brock,et al.  Elastic Strips: A Framework for Motion Generation in Human Environments , 2002, Int. J. Robotics Res..

[28]  Oliver Brock,et al.  Decomposition-based motion planning: a framework for real-time motion planning in high-dimensional configuration spaces , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).