Visual servoing control of soft robots based on finite element model

Zhang, Zhongkai; Bieze, Thor Morales; Dequidt, Jérémie; Kruszewski, Alexandre; Duriez, Christian

doi:10.1109/iros.2017.8206121

Cited by 26 publications

(21 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Combining both (10) and (16), the QP problem with the LCP (10)can be converted into a standard QP problem without the LCP: where Q = Q 1 +εQ 2 and c = c 1 +εc 2 with ε being the weight of the LCP. For general problems, the parameter ε should be chosen as a large value to make sure that the LCP holds during the optimization.…”

Section: B Fem Controller Designmentioning

confidence: 99%

“…If the FE model has a lower accuracy, the condition for a stable loop using (23) is that the error of J a does not generate an inverted mapping of J a . Then, we can increase the robustness of the system by choosing a suitable control parameters [10].…”

Section: Robot Controller Designmentioning

confidence: 99%

“…It is assumed that F 1 , F 2 , F 3 , and F 4 are the minimum value of objective functions for (10), (15), (16) and (17), respectively. λ 1 , λ 2 , λ 3 and λ 4 are respectively the solution of QP problems (10), (15), (16) and (17), respectively.…”

Section: Appendixmentioning

confidence: 99%

“…Most position controllers are designed based on the inverse kinematic model so that the computation of inverse Jacobian matrix is indispensable. Jacobian matrix can be computed based on either the analytical model [7], [8] or the numerical model [9], [10]. These methods are proposed for the position control of catheters or soft robots without considering the interaction with the environment.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Motion Control of Cable-Driven Continuum Catheter Robot Through Contacts

Zhang

Dequidt

Back

et al. 2019

IEEE Robot. Autom. Lett.

Self Cite

View full text Add to dashboard Cite

Catheter-based intervention plays an important role in minimally invasive surgery. For the closed-loop control of catheter robot through contacts, the loss of contact sensing along the entire catheter might result in task failure. To deal with this problem, we propose a decoupled motion control strategy which allows to control insertion and bending independently. We model the catheter robot and the contacts using the Finite Element Method. Then, we combine the simulated system and the real system for the closed-loop motion control. The control inputs are computed by solving a quadratic programming (QP) problem with a linear complementarity problem (LCP). A simplified method is proposed to solve this optimization problem by converting it into a standard QP problem. Using the proposed strategy, not only the control inputs but also the contact forces along the entire catheter can be computed without using force sensors. Finally, we validate the proposed methods using both simulation and experiments on a cabledriven continuum catheter robot for the real-time motion control through contacts.

show abstract

Section: B Fem Controller Designmentioning

confidence: 99%

Section: Robot Controller Designmentioning

confidence: 99%

Section: Appendixmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Motion Control of Cable-Driven Continuum Catheter Robot Through Contacts

Zhang

Dequidt

Back

et al. 2019

IEEE Robot. Autom. Lett.

Self Cite

View full text Add to dashboard Cite

show abstract

“…This paper thus proposes a cheap and general strategy for calibration and force sensing of soft robots using an RGB-D camera. Calibration and force sensing are achieved using a real-time Finite Element Method (FEM) which has been employed for position control of soft robots [4], [5]. In contrast to our previous work [6], the designed external force sensing solution is marker-free and the accuracy is improved.…”

Section: Introductionmentioning

confidence: 99%

Calibration and External Force Sensing for Soft Robots Using an RGB-D Camera

Zhang

Petit

Dequidt

et al. 2019

IEEE Robot. Autom. Lett.

Self Cite

View full text Add to dashboard Cite

Benefiting from the deformability of soft robots, calibration and force sensing for soft robots are possible using an external vision-based system, instead of embedded mechatronic force sensors. In this paper, we first propose a calibration method to calibrate both the sensor-robot coordinate system and the actuator inputs. This task is addressed through a sequential optimization problem for both variables. We also introduce an external force sensing system based on a realtime Finite Element (FE) model with the assumption of static configurations, and which consists of two steps: force location detection and force intensity computation. The algorithm that estimates force location relies on the segmentation of the point cloud acquired by an RGB-D camera. Then, the force intensities can be computed by solving an inverse quasi-static problem based on matching the FE model with the point cloud of the soft robot. As for validation, the proposed strategies for calibration and force sensing have been tested using a parallel soft robot driven by four cables.

show abstract

A Soft Collaborative Robot for Contact‐based Intuitive Human Drag Teaching

Gong,

Li,

et al. 2024

Advanced Science

View full text Add to dashboard Cite

Soft material‐based robots, known for their safety and compliance, are expected to play an irreplaceable role in human‐robot collaboration. However, this expectation is far from real industrial applications due to their complex programmability and poor motion precision, brought by the super elasticity and large hysteresis of soft materials. Here, a soft collaborative robot (Soft Co‐bot) with intuitive and easy programming by contact‐based drag teaching, and also with exceptional motion repeatability (< 0.30% of body length) and ultra‐low hysteresis (< 2.0%) is reported. Such an unprecedented capability is achieved by a biomimetic antagonistic design within a pneumatic soft robot, in which cables are threaded to servo motors through tension sensors to form a self‐sensing system, thus providing both precise actuation and dragging‐aware collaboration. Hence, the Soft Co‐bots can be first taught by human drag and then precisely repeat various tasks on their own, such as electronics assembling, machine tool installation, etc. The proposed Soft Co‐bots exhibit a high potential for safe and intuitive human‐robot collaboration in unstructured environments, promoting the immediate practical application of soft robots.

show abstract

Visual servoing control of soft robots based on finite element model

Cited by 26 publications

References 23 publications

Motion Control of Cable-Driven Continuum Catheter Robot Through Contacts

Motion Control of Cable-Driven Continuum Catheter Robot Through Contacts

Calibration and External Force Sensing for Soft Robots Using an RGB-D Camera

A Soft Collaborative Robot for Contact‐based Intuitive Human Drag Teaching

Contact Info

Product

Resources

About