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Michael E. Henderson

dblp:67/4149 · DBLP profile ↗
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3ranked-venue papers
1as first author
0since 2021 · last 2013
0009-0007-2206-0011ORCID · corroborated

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

Systems, architecture and hardware · 2 · 1 first-authorArtificial intelligence and machine learning · 1Applied, interdisciplinary, general and emerging computing · 1

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 · 69% Robot manipulation · 18% Optimization for machine learning · 13%

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

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control
path planning
0.322013
Planning Singularity-Free Paths on Closed-Chain Manipulators · IEEE Trans. Robotics 2013
A singularity-free path planner for closed-chain manipulators · ICRA 2012
Robotics › Motion planning and robot control › manipulator motion planning
singularity-free path planning
0.322013
Planning Singularity-Free Paths on Closed-Chain Manipulators · IEEE Trans. Robotics 2013
A singularity-free path planner for closed-chain manipulators · ICRA 2012
Robotics › Robot manipulation › parallel manipulator
closed-chain manipulator
0.222013
A singularity-free path planner for closed-chain manipulators · ICRA 2012
Planning Singularity-Free Paths on Closed-Chain Manipulators · IEEE Trans. Robotics 2013
Robotics › Motion planning and robot control › motion planning
configuration space
0.112012
A singularity-free path planner for closed-chain manipulators · ICRA 2012
Machine learning › Optimization for machine learning
homotopy methods
0.112012
A singularity-free path planner for closed-chain manipulators · ICRA 2012

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

smooth manifold · 0.2continuation techniques · 0.2higher-dimensional continuation · 0.1
YearPublicationVenuePosition
2013 Planning Singularity-Free Paths on Closed-Chain Manipulators
abstract
This paper provides an algorithm for computing singularity-free paths on closed-chain manipulators. Given two nonsingular configurations of the manipulator, the method attempts to connect them through a path that maintains a minimum clearance with respect to the singularity locus at all points, which guarantees the controllability of the manipulator everywhere along the path. The method can be applied to nonredundant manipulators of general architecture, and it is resolution complete. It always returns a path whenever one exists at a given resolution or determines path nonexistence otherwise. The strategy relies on defining a smooth manifold that maintains a one-to-one correspondence with the singularity-free C-space of the manipulator, and on using a higher dimensional continuation technique to explore this manifold systematically from one configuration, until the second configuration is found. If desired, the method can also be used to compute an exhaustive atlas of the whole singularity-free component reachable from a given configuration, which is useful to rapidly resolve subsequent planning queries within such component, or to visualize the singularity-free workspace of any of the manipulator coordinates. Examples are included that demonstrate the performance of the method on illustrative situations.
Oriol Bohigas, Michael E. Henderson, Lluís Ros, Montserrat Manubens, Josep M. Porta
IEEE Trans. Robotics2
2012 A singularity-free path planner for closed-chain manipulators
abstract
This paper provides an algorithm for computing singularity-free paths on non-redundant closed-chain manipulators. Given two non-singular configurations of the manipulator, the method attempts to connect them through a configuration space path that maintains a minimum clearance with respect to the singularity locus at all points. The method is resolution-complete, in the sense that it always returns a path if one exists at a given resolution, or returns “failure” otherwise. The path is computed by defining a new manifold that maintains a one-to-one correspondence with the singularity-free configuration space of the manipulator, and then using a higher-dimensional continuation technique to explore this manifold systematically from one configuration, until the second configuration is found. Examples are included that demonstrate the performance of the method on illustrative situations.
Oriol Bohigas, Michael E. Henderson, Lluís Ros, Josep M. Porta
ICRA2
1989 Synergy in parallel algorithms
Michael E. Henderson, Willard L. Miranker
Parallel Comput.1