Recurrent fuzzy wavelet neural networks based on robust adaptive sliding mode control for industrial robot manipulators

Yen, Vu Thi; Wang, Nan; Cuong, Pham Van

doi:10.1007/s00521-018-3520-3

Cited by 104 publications

(50 citation statements)

References 37 publications

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“…All experiments were performed on a flat terrain. Ren et al, 2014;Cully et al, 2015;Rubio et al, 2018Rubio et al, , 2019Yen et al, 2018) required a considerable amount of time (more than several tens of seconds) to respond to unexpected physical damage. Meanwhile, we have recently developed a brittle starlike robot that can immediately adapt to unexpected physical damage , yet the number of degrees of freedom within the body was still small.…”

Section: Discussionmentioning

confidence: 99%

“…The challenge now is how to make the robots coordinate, in real-time, their numerous bodily degrees of freedom under unpredictable circumstances, including changes in the environment and unexpected physical damages to the robots' structure. Previous studies tackled this problem by using learning techniques (Bongard et al, 2006;Mahdavi and Bentley, 2006;Mostafa et al, 2010;Koos et al, 2013;Christensen et al, 2014;Ren et al, 2014;Rubio et al, 2018Rubio et al, , 2019Yen et al, 2018) and trial-and-error methods (Cully et al, 2015), however, the performance level of robots using these techniques is not satisfactory. Specifically, the previous robots could only adapt to predictable circumstances or required a considerably long adaptation time.…”

Section: Introductionmentioning

confidence: 99%

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Flexible Coordination of Flexible Limbs: Decentralized Control Scheme for Inter- and Intra-Limb Coordination in Brittle Stars' Locomotion

et al. 2019

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Conventional mobile robots have difficulties adapting to unpredictable environments or performing adequately after undergoing physical damages in realtime operation, unlike animals. We address this issue by focusing on brittle stars, an echinoderm related to starfish. Most brittle stars have five flexible arms, and they can coordinate among the arms (i.e., inter-arm coordination) as well as the many bodily degrees of freedom within each arm (i.e., intra-arm coordination). They can move in unpredictable environments while promptly adapting to those, and to their own physical damages (e.g., arm amputation). Our previous work focused on the inter-arm coordination by studying trimmed-arm brittle stars. Herein, we extend our previous work and propose a decentralized control mechanism that enables coupling between the inter-arm and intra-arm coordination. We demonstrate via simulations and real-world experiments with a brittle star-like robot that the behavior of brittle stars when they are intact and undergoing shortening or amputation of arms can be replicated.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Flexible Coordination of Flexible Limbs: Decentralized Control Scheme for Inter- and Intra-Limb Coordination in Brittle Stars' Locomotion

et al. 2019

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“…In teaching STEM (Science, Technology, Engineering, and Mathematics), learning about nanotechnology has gained popularity by implementing visuohaptic simulations of point charges and their interactions. Students in visuohaptic (VH) groups were more motivated and developed positive attitude toward learning than their peers in visual-only (V) groups (Park et al, 2010;Rubio, 2012;Rubio et al, 2018;Yen et al, 2018).…”

Section: Related Workmentioning

confidence: 99%

Visual-Haptic Size Estimation in Peripersonal Space

2020

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In perceptual psychology, estimations of visual depth and size under different spatial layouts have been extensively studied. However, research evidence in virtual environments (VE) is relatively lacking. The emergence of human-computer interaction (HCI) and virtual reality (VR) has raised the question of how human operators perform actions based on the estimation of visual properties in VR, especially when the sensory cues associated with the same object are conflicting. We report on an experiment in which participants compared the size of a visual sphere to a haptic sphere, belonging to the same object in a VE. The sizes from the visual and haptic modalities were either identical or conflicting (with visual size being larger than haptic size, or vice versa). We used three standard haptic references (small, medium, and large sizes) and asked participants to compare the visual sizes with the given reference, by method of constant stimuli. Results show a dominant functional priority of the visual size perception. Moreover, observers demonstrated a central tendency effect: over-estimation for smaller haptic sizes but under-estimation for larger haptic sizes. The results are in-line with previous studies in real environments (RE). We discuss the current findings in the framework of adaptation level theory for haptic size reference. This work provides important implications for the optimal design of human-computer interactions when integrating 3D visual-haptic information in a VE.

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“…For example, position exchange is an algorithm that estimates the forces based on the error between the desired position of the robot and the actual (current) position of the robot (Siciliano and Khatib, 2016). Other studies suggested more advanced haptic feedback estimation algorithms for RAMIS (Anooshahpour et al, 2014;Dalvand et al, 2014;Li and Hannaford, 2017;Rivero et al, 2017), as well as advanced algorithms for learning the dynamics of robots that can be modified to cable-driven robots (Rubio, 2012;García-Sánchez et al, 2018;He and Dong, 2018;Rubio et al, 2018;Yen et al, 2018). Each one of the force feedback algorithms has a trade-off between system stability and transparency along with other limitations.…”

Section: Introductionmentioning

confidence: 99%

Surgeon-Centered Analysis of Robot-Assisted Needle Driving Under Different Force Feedback Conditions

2020

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Robotic assisted minimally invasive surgery (RAMIS) systems present many advantages to the surgeon and patient over open and standard laparoscopic surgery. However, haptic feedback, which is crucial for the success of many surgical procedures, is still an open challenge in RAMIS. Understanding the way that haptic feedback affects performance and learning can be useful in the development of haptic feedback algorithms and teleoperation control systems. In this study, we examined the performance and learning of inexperienced participants under different haptic feedback conditions in a task of surgical needle driving via a soft homogeneous deformable object-an artificial tissue. We designed an experimental setup to characterize their movement trajectories and the forces that they applied on the artificial tissue. Participants first performed the task in an open condition, with a standard surgical needle holder, followed by teleoperation in one of three feedback conditions: (1) no haptic feedback, (2) haptic feedback based on position exchange, and (3) haptic feedback based on direct recording from a force sensor, and then again with the open needle holder. To quantify the effect of different force feedback conditions on the quality of needle driving, we developed novel metrics that assess the kinematics of needle driving and the tissue interaction forces, and we combined our novel metrics with classical metrics. We analyzed the final teleoperated performance in each condition, the improvement during teleoperation, and the aftereffect of teleoperation on the performance when using the open needle driver. We found that there is no significant difference in the final performance and in the aftereffect between the 3 conditions. Only the two conditions with force feedback presented statistically significant improvement during teleoperation in several of the metrics, but when we compared directly between the improvements in the three different feedback conditions none of the effects reached statistical significance. We discuss possible explanations for the relative similarity in performance. We conclude that we developed several new metrics for the quality of surgical needle driving, but even with these detailed metrics, the advantage of state of the art force feedback methods to tasks that require interaction with homogeneous soft tissue is questionable.

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Recurrent fuzzy wavelet neural networks based on robust adaptive sliding mode control for industrial robot manipulators

Cited by 104 publications

References 37 publications

Flexible Coordination of Flexible Limbs: Decentralized Control Scheme for Inter- and Intra-Limb Coordination in Brittle Stars' Locomotion

Flexible Coordination of Flexible Limbs: Decentralized Control Scheme for Inter- and Intra-Limb Coordination in Brittle Stars' Locomotion

Visual-Haptic Size Estimation in Peripersonal Space

Surgeon-Centered Analysis of Robot-Assisted Needle Driving Under Different Force Feedback Conditions

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