Evidence map›Paper›PMID 37631577›Full record

ArticleSensors (Basel, Switzerland)2023

Depth-Dependent Control in Vision-Sensor Space for Reconfigurable Parallel Manipulators.

Arturo Franco-López, Mauro Maya, Alejandro González, Antonio Cardenas, Davide Piovesan

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Arturo Franco-LópezFacultad de Ingenieria, Universidad Autonoma de San Luis Potosi, San Luis Potosi 78290, Mexico.
Mauro MayaFacultad de Ingenieria, Universidad Autonoma de San Luis Potosi, San Luis Potosi 78290, Mexico.ORCID 0000-0002-4548-8666
Alejandro GonzálezEscuela de Ingeniería y Ciencias, Tecnologico de Monterrey, Querétaro 76130, Mexico.ORCID 0000-0001-6803-9719
Antonio CardenasFacultad de Ingenieria, Universidad Autonoma de San Luis Potosi, San Luis Potosi 78290, Mexico.ORCID 0000-0003-4208-0566
Davide PiovesanBiomedical, Industrial and Systems Engineering Department, Gannon University, Erie, PA 16541, USA.ORCID 0000-0002-9258-8985

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this paper, a control approach for reconfigurable parallel robots is designed. Based on it, controls in the vision-sensor, 3D and joint spaces are designed and implemented in target tracking tasks in a novel reconfigurable delta-type parallel robot. No a priori information about the target trajectory is required. Robot reconfiguration can be used to overcome some of the limitations of parallel robots like small relative workspace or multiple singularities, at the cost of increasing the complexity of the manipulator, making its control design even more challenging. No general control methodology exists for reconfigurable parallel robots. Tracking objects with unknown trajectories is a challenging task required in many applications. Sensor-based robot control has been actively used for this type of task. However, it cannot be straightforwardly extended to reconfigurable parallel manipulators. The developed vision-sensor space control is inspired by, and can be seen as an extension of, the Velocity Linear Camera Model-Camera Space Manipulation (VLCM-CSM) methodology. Several experiments were carried out on a reconfigurable delta-type parallel robot. An average positioning error of 0.6 mm was obtained for static objectives. Tracking errors of 2.5 mm, 3.9 mm and 11.5 mm were obtained for targets moving along a linear trajectory at speeds of 6.5, 9.3 and 12.7 cm/s, respectively. The control cycle time was 16 ms. These results validate the proposed approach and improve upon previous works for non-reconfigurable robots.

Indexed as

camera-space manipulationparallel robotvision-based control

Identifiers

PMID37631577
PMCPMC10459706

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.