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Lukas Stadelmann

dblp:194/2781 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2017
0000-0002-7173-7259ORCID · reported

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

Artificial intelligence and machine learning · 1Systems, architecture and hardware · 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
1 paper
Motion planning and robot control · 87% Robot manipulation · 13%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control › robot control › optimal control
constrained optimal control
0.312017
Efficient kinematic planning for mobile manipulators with non-holonomic constraints using optimal control · ICRA 2017
Robotics › Motion planning and robot control
trajectory optimization
0.312017
Efficient kinematic planning for mobile manipulators with non-holonomic constraints using optimal control · ICRA 2017
Robotics › Robot manipulation
mobile manipulation
0.112017
Efficient kinematic planning for mobile manipulators with non-holonomic constraints using optimal control · ICRA 2017

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

sequential linear quadratic optimal control · 0.3receding horizon control · 0.3
YearPublicationVenuePosition
2017 Efficient kinematic planning for mobile manipulators with non-holonomic constraints using optimal control
abstract
This work addresses the problem of kinematic trajectory planning for mobile manipulators with non-holonomic constraints, and holonomic operational-space tracking constraints. We obtain whole-body trajectories and time-varying kinematic feedback controllers by solving a Constrained Sequential Linear Quadratic Optimal Control problem. The employed algorithm features high efficiency through a continuous-time formulation that benefits from adaptive step-size integrators and through linear complexity in the number of integration steps. In a first application example, we solve kinematic trajectory planning problems for a 26 DoF wheeled robot. In a second example, we apply Constrained SLQ to a real-world mobile manipulator in a receding-horizon optimal control fashion, where we obtain optimal controllers and plans at rates up to 100 Hz.
Markus Giftthaler, Farbod Farshidian, Timothy Sandy, Lukas Stadelmann, Jonas Buchli
ICRA4