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On Fast Jerk–, Acceleration– and Velocity–Restricted Motion Functions for Online Trajectory Generation

Burkhard Alpers

2021Robotics31 citationsDOIOpen Access PDF

Abstract

Finding fast motion functions to get from an initial state (distance, velocity, acceleration) to a final one has been of interest for decades. For a solution to be practically relevant, restrictions on jerk, acceleration and velocity have to be taken into account. Such solutions use optimization algorithms or try to directly construct a motion function allowing online trajectory generation. In this contribution, we follow the latter strategy and present an approach which first deals with the situation where initial and final accelerations are 0, and then relates the general case as much as possible to this situation. This leads to a classification with just four major cases. A continuity argument guarantees full coverage of all situations which is not the case or is not clear for other available algorithms. We present several examples that show the variety of different situations and, thus, the complexity of the task. We also describe an implementation in MATLAB® and results from a huge number of test runs regarding accuracy and efficiency, thus demonstrating that the algorithm is suitable for online trajectory generation.

Topics & Concepts

JerkAccelerationTrajectoryMotion (physics)Computer scienceFunction (biology)Task (project management)Control theory (sociology)Construct (python library)Online algorithmMATLABAlgorithmVariety (cybernetics)MathematicsArtificial intelligenceEngineeringControl (management)PhysicsClassical mechanicsEvolutionary biologyBiologyProgramming languageAstronomySystems engineeringOperating systemRobotic Path Planning AlgorithmsTeaching and Learning ProgrammingRobotic Mechanisms and Dynamics
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