Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page
Demo Data from SIGIR 2026 / reviewers in the wild / expert

Adam Ratajczak

dblp:63/8718 · DBLP profile ↗
← Back
1ranked-venue papers
1as first author
0since 2021 · last 2011
0000-0001-9376-0129ORCID · reported

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-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
1 paper
Motion planning and robot control · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control
motion planning		 0.112011
Motion planning of a balancing robot with threefold sub-tasks: An endogenous configuration space approach · ICRA 2011
Robotics › Motion planning and robot control › robot control › stabilization control
balancing robot control		 0.012011
Motion planning of a balancing robot with threefold sub-tasks: An endogenous configuration space approach · ICRA 2011

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

endogenous configuration space approach · 0.1
YearPublicationVenuePosition
2011 Motion planning of a balancing robot with threefold sub-tasks: An endogenous configuration space approach
abstract
The paper presents a task-priority motion planning algorithm for a balancing robot, derived from the endogenous configuration space approach. The motion planning problem is composed of three sub-tasks. Firstly, the robot has to reach a desirable point in task space (proper motion planning). Secondly, the upward position of the robot torso should be maintained during the motion. Thirdly, the motion should save the control energy. Performance of our algorithm is presented in simulations.
Adam Ratajczak, Krzysztof Tchon
 ICRA1