2020
DOI: 10.1109/access.2020.3041616
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Nonlinear Model Predictive Growth Control of a Class of Plant-Inspired Soft Growing Robots

Abstract: Recently, researchers have shown an increased interest in considering plants as a model of inspiration for designing new robot locomotions. Growing robots, that imitate the biological growth presented by plants, have proved irresistible in unpredictable and distal environments due to their morphological adaptation and tip-extension capabilities. However, as a result of the irreversible growing process exhibited by growing robots, classical control schemes could fail in obtaining feasible solutions that respect… Show more

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Cited by 15 publications
(10 citation statements)
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“…where α g is constant gain, x g 0 is the new goal position. Similarly, the goal orientation q g in ( 10) varies with time to keep up with orientation discontinuity that occurs due to goal variation and is calculated as follows: τ qg = α g 0 log(q g 0 qg )q g (15) where α g 0 ∈ R 4×4 is positive diagonal gain matrix and q g 0 is the new goal orientation. As depicted in Fig.…”
Section: B Ibmp Representation Of Robot Tip Orientationmentioning
confidence: 99%
See 1 more Smart Citation
“…where α g is constant gain, x g 0 is the new goal position. Similarly, the goal orientation q g in ( 10) varies with time to keep up with orientation discontinuity that occurs due to goal variation and is calculated as follows: τ qg = α g 0 log(q g 0 qg )q g (15) where α g 0 ∈ R 4×4 is positive diagonal gain matrix and q g 0 is the new goal orientation. As depicted in Fig.…”
Section: B Ibmp Representation Of Robot Tip Orientationmentioning
confidence: 99%
“…On the other hand, developing a control algorithm for continuum manipulators that can successfully interact robustly with dynamic environments is challenging [15]. Nonlinear hybrid position/force control of a tendon-driven catheter was presented in [16].…”
mentioning
confidence: 99%
“…Proof : Note first that substituting the control law ( 14) into (2) yields (11) with the parameters (13)…”
Section: B Control Lawmentioning
confidence: 99%
“…To date few results are available on model based control of soft growing robots [9]. Similarly to other soft robots, kinematic models [10] and kinematic-based controllers can be appropriate if a fast response is not required [8], [11]- [13]. In general however, dynamical models and corresponding model based controllers allow improving the transient performance of soft robots and can compensate the effects of external forces This research was supported by the Engineering and Physical Sciences Research Council (grant EP/W004224/1 and grant EP/R511547/1).…”
Section: Introductionmentioning
confidence: 99%
“…The MHE can consider state and output constraints imposed by the irreversible growing nature of vine robots in contrast to the EKF while relying on the most recent measurements window, i.e., the Markovian assumption is relaxed. In contrast to our previous work in [21], this paper has not assumed that the entire robot's state is known and instead estimated the state in an online fashion. Additionally, thanks to the state estimation of MHE, an NMPC as a class of optimal control is proposed to handle the multiple-input, multiple-output nonlinear model of the vine robot.…”
Section: Introductionmentioning
confidence: 99%