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Record W4365129215 · doi:10.1109/tmech.2023.3263108

Noncollocated Proprioceptive Sensing for Lightweight Flexible Robotic Manipulators

2023· article· en· W4365129215 on OpenAlexaff
Xavier Garant, Clément Gosselin

Bibliographic record

VenueIEEE/ASME Transactions on Mechatronics · 2023
Typearticle
Languageen
FieldEngineering
TopicRobot Manipulation and Learning
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsSerial manipulatorKinematicsComputer scienceEncoderActuatorControl engineeringRobotic armContext (archaeology)Redundancy (engineering)WorkspaceKinematic chainRobot end effectorRobotMobile manipulatorFlexibility (engineering)Control theory (sociology)SimulationParallel manipulatorEngineeringArtificial intelligenceControl (management)Mobile robot

Abstract

fetched live from OpenAlex

This article presents the design of a noncollocated feedback system for flexible serial manipulators. The device is a passive serial chain of encoders and lightweight links, mounted in parallel with the manipulator. This measuring arm effectively decouples the manipulator's proprioception from its actuators by providing information on the actual end effector pose, accounting for both joint and link flexibility. The kinematic redundancy of the measuring chain allows for safe operation in the context of human–robot interaction. A simple yet effective error model is introduced to assess the suitability of the proposed sensor system in the context of robotic control. The practicality of the device is first demonstrated by building a physical joint-encoder assembly and a simplified planar measuring arm prototype. With this additional feedback, a task-space position controller is devised and tested in simulation. Finally, the simulation results are validated with an experimental 3-DoF lightweight manipulator prototype equipped with a five-joint measuring arm.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.977
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.031
GPT teacher head0.255
Teacher spread0.224 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2023
Admission routes1
Has abstractyes

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