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Sonja E. Macfarlane

dblp:26/6547 · DBLP profile ↗
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2ranked-venue papers
2as first author
0since 2021 · last 2003
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 first-authorSystems, architecture and hardware · 1 · 1 first-authorApplied, interdisciplinary, general and emerging computing · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
2 papers
Motion planning and robot control · 95% Robot manipulation · 5%

Topics — the 5 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control
trajectory planning
0.122003
Jerk-bounded manipulator trajectory planning: design for real-time applications · IEEE Trans. Robotics Autom. 2003
Design of Jerk Bounded Trajectories for On-Line Industrial Robot Applications · ICRA 2001
Robotics › Motion planning and robot control › trajectory planning
jerk-limited trajectory
0.012001
Design of Jerk Bounded Trajectories for On-Line Industrial Robot Applications · ICRA 2001
Robotics › Motion planning and robot control › motion planning
online motion planning
0.012003
Jerk-bounded manipulator trajectory planning: design for real-time applications · IEEE Trans. Robotics Autom. 2003
Robotics › Motion planning and robot control › motion planning › real-time motion planning
real-time trajectory generation
0.012003
Jerk-bounded manipulator trajectory planning: design for real-time applications · IEEE Trans. Robotics Autom. 2003
Robotics › Robot manipulation
industrial robot
0.012001
Design of Jerk Bounded Trajectories for On-Line Industrial Robot Applications · ICRA 2001

Methods — techniques the papers use, named apart from their topics

sine wave template · 0.0quintic polynomial concatenation · 0.0parabolic blend approximation · 0.0sine wave approximation · 0.0quintic polynomial · 0.0
YearPublicationVenuePosition
2003 Jerk-bounded manipulator trajectory planning: design for real-time applications
abstract
An online method for obtaining smooth, jerk-bounded trajectories has been developed and implemented. Jerk limitation is important in industrial robot applications, since it results in improved path tracking and reduced wear on the robot. The method described herein uses a concatenation of fifth-order polynomials to provide a smooth trajectory between two way points. The trajectory approximates a linear segment with parabolic blends trajectory. A sine wave template is used to calculate the end conditions (control points) for ramps from zero acceleration to nonzero acceleration. Joining these control points with quintic polynomials results in a controlled quintic trajectory that does not oscillate, and is near time optimal for the jerk and acceleration limits specified. The method requires only the computation of the quintic control points, up to a maximum of eight points per trajectory way point. This provides hard bounds for online motion algorithm computation time. A method for blending these straight-line trajectories over a series of way points is also discussed. Simulations and experimental results on an industrial robot are presented.
Sonja E. Macfarlane, Elizabeth A. Croft
IEEE Trans. Robotics Autom.1
2001 Design of Jerk Bounded Trajectories for On-Line Industrial Robot Applications
abstract
An online method for obtaining smooth, jerk-bounded trajectories has been developed and implemented. Jerk limitation is important in industrial robot applications, since it results in improved path tracking and reduced wear on the robot. The method described herein uses a concatenation of fifth-order polynomials to provide a smooth trajectory between two points. The trajectory is determined based on approximating a linear segment with parabolic blends trajectory. A sine wave approximation is used to ramp from zero acceleration to non-zero acceleration. This results in a controlled quintic trajectory which does not oscillate, and is near time-optimal given the jerk and acceleration limits specified. The method requires only the computation of the quintic control points, up to a maximum of seven points per trajectory way-point. This provides hard bounds for online motion algorithm computation time. Simulations and experimental results on an industrial robot are presented.
Sonja E. Macfarlane, Elizabeth A. Croft
ICRA1