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Record W7161977890 · doi:10.82308/3118

Development of fast pick-and-place robots

2018· dissertation· en· W7161977890 on OpenAlexaboutno aff
Peyman Karimi Eskandary

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicRobotic Mechanisms and Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsParallelogramKinematicsLinkage (software)RobotRealization (probability)Development (topology)Translation (biology)Generator (circuit theory)Robot kinematics

Abstract

fetched live from OpenAlex

Industry calls upon fast pick-and-place robots with high precision and maneuverability. A parallel architecture was recently proposed to generate Schönflies motions, with a CRRHHRRC[1] closed kinematic chain, that offers a functionally symmetric, single-loop, architecture, with an isostatic kinematic chain, and virtually unlimited rotatability of its gripper. This robot calls for a cylindrical drive, i.e., a two-degree-of-freedom cylindrical actuator. The thesis reports the comprehensive mechanical design, besides the kinematics and dynamics analyses of the above-mentioned mechanical system, a Schönflies-motion generator (SMG), developed at McGill University's Centre for Intelligent Machines. The analysis is intended to optimize the robot design, and examine the new ideas for speeding up its operation. Validation of the mathematical model was conducted experimentally. The results reveal the pertinence of the model.The author introduces a novel drive, dubbed the translating Π-joint, to be used as a cylindrical drive targeting the pick-and-place operations of the SMG. It is first recalled that a Π-joint is a parallelogram four-bar linkage whose coupler link undergoes pure translation w.r.t. its fixed link; moreover, all the points of the coupler link describe circles with identical radii, the common length of the two other links. The translating Π-joint is the series array of a prismatic and a Π-joint, the plane of latter being normal to the direction of the former. A realization of the translating Π-joint is the RHRRHR kinematic chain. Furthermore, four implementations are disclosed, each with unique features. In addition, the applications of this joint are studied, including two novel architectures for SMGs. The detailed design and fabrication of two prototypes based on the above-mentioned implementations is reported.In addition, the concept of virtual screw is introduced in this thesis. The virtual screw is constructed by means of cable mechanisms. The virtual screw is to be used whenever a screw joint with very large pitch is needed, in light of the limitations in the pitch sizes (a few mm/turn) available in off-the-shelf screw mechanisms. This concept arose as an alternative to the usual screw joint when designing a cylindrical differential mechanism made of lead or ball screws, with zero backlash and adjustable speed ratio. First, the virtual screw was introduced to turn the gripper of the above-mentioned SMG, originally driven by means of two coaxial right- and left-hand screws. Later, the application of the virtual screw was extended to the cylindrical drive. The conceptual and detailed designs are disclosed here.[1] C, R and H standing for cylindrical, revolute and screw joint, respectively, underlines indicating an actuated joint.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.007
GPT teacher head0.213
Teacher spread0.206 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations0
Published2018
Admission routes1
Has abstractyes

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