You will be provided with a reference and some statements. Please determine whether each statement is 'supported', 'unsupported', or 'unknown' with respect to the reference. Please note:
First, assess whether the reference contains any valid content. If the reference contains no valid information, such as a 'page not found' message, then all statements should be considered 'unknown'.
If the reference is valid, for a given statement: if the facts or data it contains can be found entirely or partially within the reference, it is considered 'supported' (data accepts rounding); if all facts and data in the statement cannot be found in the reference, it is considered 'unsupported'.

You should return the result in a JSON list format, where each item in the list contains the statement's index and the judgment result, for example:
[
    {
        "idx": 1,
        "result": "supported"
    },
    {
        "idx": 2,
        "result": "unsupported"
    }
]

Below are the reference and statements:
<reference>
[2011.01408] Hybrid Visual Servoing Tracking Control of Uncalibrated Robotic Systems for Dynamic Dwarf Culture Orchards Harvest

Abstract page for arXiv paper 2011.01408: Hybrid Visual Servoing Tracking Control of Uncalibrated Robotic Systems for Dynamic Dwarf Culture Orchards Harvest

Skip to main content

Search

Submit

Donate

Log in

Search arXiv

Press Enter to search ·
Advanced search

Computer Science > Robotics

arXiv:2011.01408
(cs)

[Submitted on 3 Nov 2020 (
v1
), last revised 10 Jun 2021 (this version, v2)]

Title:
Hybrid Visual Servoing Tracking Control of Uncalibrated Robotic Systems for Dynamic Dwarf Culture Orchards Harvest

Authors:
Tao Li
,
Quan Qiu
,
Chunjiang Zhao

View a PDF of the paper titled Hybrid Visual Servoing Tracking Control of Uncalibrated Robotic Systems for Dynamic Dwarf Culture Orchards Harvest, by Tao Li and Quan Qiu and Chunjiang Zhao

View PDF

HTML (experimental)

Abstract:
The paper is concerned with the dynamic tracking problem of SNAP orchards harvesting robots in the presence of multiple uncalibrated model parameters in the application of dwarf culture orchards harvest. A new hybrid visual servoing adaptive tracking controller and three adaptive laws are proposed to guarantee harvesting robots to finish the dynamic harvesting task and the adaption to unknown parameters including camera intrinsic and extrinsic model and robot dynamics. By the Lyapunov theory, asymptotic convergence of the closed-loop system with the proposed control scheme is rigorously proven. Experimental and simulation results have been conducted to verify the performance of the proposed control scheme. The results demonstrate its effectiveness and superiority.

Comments:

6 pages,15 figures, accepted by IEEE ICDL2021

Subjects:

Robotics (cs.RO)
; Systems and Control (eess.SY)

MSC
classes:

70B15, 70E60, 70Q05, 93C85

Cite as:

arXiv:2011.01408
[cs.RO]

(or

arXiv:2011.01408v2
[cs.RO]
for this version)

https://doi.org/10.48550/arXiv.2011.01408

Focus to learn more

arXiv-issued DOI via DataCite

Submission history
From: Tao Li [
view email
]

[v1]

Tue, 3 Nov 2020 01:32:18 UTC (10,971 KB)

[v2]

Thu, 10 Jun 2021 08:48:57 UTC (5,933 KB)

Full-text links:

Access Paper:

View a PDF of the paper titled Hybrid Visual Servoing Tracking Control of Uncalibrated Robotic Systems for Dynamic Dwarf Culture Orchards Harvest, by Tao Li and Quan Qiu and Chunjiang Zhao
View PDF
HTML (experimental)
TeX Source

view license

Current browse context:

cs.RO

< prev

|

next >

new

|

recent

|
2020-11

Change to browse by:

cs

cs.SY

eess

eess.SY

References & Citations

NASA ADS
Google Scholar

Semantic Scholar

DBLP
- CS Bibliography

listing
|
bibtex

Tao Li

export BibTeX citation

Loading...

BibTeX formatted citation

×

loading...

Data provided by:

Bookmark

Bibliographic Tools

Bibliographic and Citation Tools

Bibliographic Explorer Toggle

Bibliographic Explorer

(
What is the Explorer?
)

Connected Papers Toggle

Connected Papers

(
What is Connected Papers?
)

Litmaps Toggle

Litmaps

(
What is Litmaps?
)

scite.ai Toggle

scite Smart Citations

(
What are Smart Citations?
)

Code, Data, Media

Code, Data and Media Associated with this Article

alphaXiv Toggle

alphaXiv

(
What is alphaXiv?
)

Links to Code Toggle

CatalyzeX Code Finder for Papers

(
What is CatalyzeX?
)

DagsHub Toggle

DagsHub

(
What is DagsHub?
)

GotitPub Toggle

Gotit.pub

(
What is GotitPub?
)

Huggingface Toggle

Hugging Face

(
What is Huggingface?
)

ScienceCast Toggle

ScienceCast

(
What is ScienceCast?
)

Demos

Demos

Replicate Toggle

Replicate

(
What is Replicate?
)

Spaces Toggle

Hugging Face Spaces

(
What is Spaces?
)

Spaces Toggle

TXYZ.AI

(
What is TXYZ.AI?
)

Related Papers

Recommenders and Search Tools

Link to Influence Flower

Influence Flower

(
What are Influence Flowers?
)

Core recommender toggle

CORE Recommender

(
What is CORE?
)

Author

Venue

Institution

Topic

About arXivLabs

arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community?
Learn more about arXivLabs
.

Which authors of this paper are endorsers?
|

Disable MathJax
(
What is MathJax?
)

We gratefully acknowledge support from
our
major funders
,

member institutions
,
,
and all contributors.

About

·

Help

·

Contact

·

Subscribe

·

Copyright

·

Privacy

·

Accessibility

·

Operational Status
(opens in new tab)

Major funding support from
</reference>

<statements>
1. The evidence supports three load-bearing conclusions, each developed below from quantified pipeline results and control results.
2. hybrid visual servoing adapts unknown camera intrinsics, extrinsics and robot dynamics with Lyapunov convergence
3. recursive platform and optical state estimation
4. Hybrid visual servoing goes further: it uses three adaptive laws to estimate unknown camera intrinsics, extrinsics and robot dynamics, with Lyapunov proof of asymptotic closed-loop convergence
5. This is a natural template for an uncalibrated grain-scanning rig because camera and plant parameters are identified inside the control loop
6. The lowest layer controls physical motion and optical focus, as evidenced by adaptive visual servoing
7. The navigation layer should combine EKF fusion, adaptive visual servoing and predictive control because these methods address pose failure, uncalibrated camera and robot parameters, and unknown wheel–terrain slip.
8. Hybrid visual servoing adapts unknown camera and robot parameters with Lyapunov convergence.
9. Stability and robustness must be stated carefully
10. Hybrid visual servoing provides Lyapunov asymptotic convergence for camera and robot parameter adaptation
11. The available evidence does not establish formal frequency-domain robustness margins for a grain-imaging loop, so the design should require empirical validation under texture, illumination, motion and calibration perturbations
12. The modern-control contribution is to connect these layers: EKF and adaptive visual servoing estimate pose and camera parameters [7][8]
</statements>

Begin the assessment now. Output only the JSON list, without any conversational text or explanations.