2020
DOI: 10.3390/biomimetics5020019
|View full text |Cite
|
Sign up to set email alerts
|

Tutorial Review of Bio-Inspired Approaches to Robotic Manipulation for Space Debris Salvage

Abstract: We present a comprehensive tutorial review that explores the application of bio-inspired approaches to robot control systems for grappling and manipulating a wide range of space debris targets. Current robot manipulator control systems exploit limited techniques which can be supplemented by additional bio-inspired methods to provide a robust suite of robot manipulation technologies. In doing so, we review bio-inspired control methods because this will be the key to enabling such capabilities. In particular, fo… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

0
9
0

Year Published

2021
2021
2024
2024

Publication Types

Select...
5
1
1

Relationship

2
5

Authors

Journals

citations
Cited by 13 publications
(9 citation statements)
references
References 323 publications
(329 reference statements)
0
9
0
Order By: Relevance
“…Compared with references [16,17], the above measurement process shows that the modal number of OAM vortex waves can be easily and effectively detected by using the phase gradient method. In addition, the more the number of receiving probes, the smaller the error of the result and the higher the accuracy of the test result.…”
Section: Simulation Of Multimodal Orbital Angular Momentum Data Modelmentioning
confidence: 98%
See 1 more Smart Citation
“…Compared with references [16,17], the above measurement process shows that the modal number of OAM vortex waves can be easily and effectively detected by using the phase gradient method. In addition, the more the number of receiving probes, the smaller the error of the result and the higher the accuracy of the test result.…”
Section: Simulation Of Multimodal Orbital Angular Momentum Data Modelmentioning
confidence: 98%
“…e parameters in the traditional PID controller are constant, the system takes a long time to stabilize during the control process, and the robustness of the system output is not high. However, researchers have found that neural networks have excellent learning ability, which creates a new way to find faster and more robust adaptive controllers to adapt to disturbances and changes in related parameters and models during the control process and the impact caused by uncertainty [16][17][18].…”
Section: Related Workmentioning
confidence: 99%
“…These include, for example, the previously introduced gecko adhesion and insect-like crawling robots (Xie et al, 2021). Furthermore, bioinspired grasping and robotic manipulation have also already been discussed frequently for their use and application for on-orbit servicing and repair (Dai et al, 2020;Ellery, 2020;Ogundipe and Ellery, 2020).…”
Section: Servicing Manufacture and Assembly In Spacementioning
confidence: 99%
“…This may be exemplified by the transfer learning problem of adapting robot manipulator control on Earth to the zero-gravity environment in space. The control algorithms have the same form with minor parameter adjustments (Ellery, 2004) but neural learning of the latter requires complete re-training from new input-output data sets (Ellery, 2020 d ). Even enhancement of the backpropagation algorithm with Kalman filtering which enriches the learning process does not address this problem.…”
Section: Self-replicating Probes In Setimentioning
confidence: 99%