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

Ernest Merrill

dblp:44/5361 · DBLP profile ↗
← Back
1ranked-venue papers
0as 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 · 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 · 44% Legged, aerial and field robots · 44% Planning, search and constraint satisfaction · 13%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control › robot control › sensor-based control
proprioceptive control		 0.012003
Proprioceptive Control for a Robotic Vehicle over Geometric Obstacles · ICRA 2003
Robotics › Legged, aerial and field robots
rough terrain locomotion		 0.012003
Proprioceptive Control for a Robotic Vehicle over Geometric Obstacles · ICRA 2003
Knowledge, reasoning and agents › Planning, search and constraint satisfaction › planning › agent planning
action planning		 0.012003
Proprioceptive Control for a Robotic Vehicle over Geometric Obstacles · ICRA 2003

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

wheel torque and suspension coordination · 0.0proprioceptive algorithm · 0.0
YearPublicationVenuePosition
2003 Proprioceptive Control for a Robotic Vehicle over Geometric Obstacles
abstract
In this paper we describe a software system built to coordinate an autonomous vehicle with variable configuration ability operating in rough terrain conditions. The paper describes the system architecture, with an emphasis on the action planning function. This is intended to work with a proprioceptive algorithm that continuously coordinates wheel torques and suspension forces and positions to achieve optimal terrain crossing performance.
Kenneth J. Waldron, Ronald C. Arkin, Douglas J. Bakkum, Ernest Merrill, Muhammad E. Abdallah
 ICRA4