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Rajesh Subburaman

dblp:192/7144 · DBLP profile ↗
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2ranked-venue papers
2as first author
1since 2021 · last 2021
0000-0001-8091-6622ORCID · verified

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

Artificial intelligence and machine learning · 2 · 2 first-author · 1 since 2021Systems, architecture and hardware · 2 · 2 first-author · 1 since 2021

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% Legged, aerial and field robots · 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 › passivity-based control
energy shaping control
0.312018
Online Falling-Over Control of Humanoids Exploiting Energy Shaping and Distribution Methods · ICRA 2018
Robotics › Motion planning and robot control
robot control
0.312018
Online Falling-Over Control of Humanoids Exploiting Energy Shaping and Distribution Methods · ICRA 2018
Robotics › Legged, aerial and field robots
humanoid robot
0.112018
Online Falling-Over Control of Humanoids Exploiting Energy Shaping and Distribution Methods · ICRA 2018

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

nonlinear control · 0.3energy distribution polygons · 0.3
YearPublicationVenuePosition
2021 An Analysis on the Modeling Accuracy of Industrial Manipulators with Inherent Joint Elasticity
abstract
High precision industrial applications call for equally precise functioning of industrial manipulators, which in turn requires accurate modeling of the manipulators. This paper carries out a detailed study on the modeling of industrial manipulators with elastic joints to improve their accuracy. In particular, the effect of adopting a simple harmonic drive (HD) model and ignoring a dynamic effect called low inertia coupling between the actuators and links on the model accuracy has been analyzed from a parameter estimation perspective. Since the aforementioned model characteristics have been generally ignored for high gear reduction ratios, this study is carried out with five different reduction ratios ranging from low to high, where three different models of a three-joints elastic manipulator are considered. The accuracy of the models is compared using the torque performance metrics of a predefined joint motion of the robot. Furthermore, the impact of the models with different accuracy is assessed by carrying out a state-of-the-art dynamic parameter estimation, and the resulting errors are compared to ascertain the merits of adopting a detailed elastic dynamic model of a manipulator.
Rajesh Subburaman, Mariapaola D'Imperio, Jinoh Lee, Ferdinando Cannella
IROS1
2018 Online Falling-Over Control of Humanoids Exploiting Energy Shaping and Distribution Methods
abstract
This paper proposes a novel fall control technique based on energy concepts, which can be applied online to mitigate the impact forces incurred during the falling over of humanoids. The technique reduces the total energy using a nonlinear control tool, called energy shaping (ES), and further distributes the reduced energy over multiple contacts by means of energy distribution polygons (EDP). We also include an effective orientation control to safeguard the end-effectors in the event of ground impacts. The performance of the proposed method is numerically evaluated by dynamic simulations under the sudden falling over scenario of the humanoid robot for both lateral and sagittal falls. The effectiveness of the proposed ES and EDP concepts are verified by diverse comparative simulations with total energy, distribution, and impact forces.
Rajesh Subburaman, Jinoh Lee, Darwin G. Caldwell, Nikolaos G. Tsagarakis
ICRA1