Parameter estimation and modeling of a pneumatic continuum manipulator with asymmetric building blocks

Uppalapati, Naveen Kumar; Singh, Govindra; Krishnan, Girish

doi:10.1109/robosoft.2018.8405380

Cited by 17 publications

(15 citation statements)

References 19 publications

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“…The advantages associated with the design is promising for agriculal applications such as autonomous berry harvesting, weeding, and pruning. Our preliminary investigations [5], [6] of the manipulator reveal large nonlinear elastic deformation, with stiffness varying as a function of applied pressure. Furthermore, there exists elastic coupling between the different actuators, and sizable attenuation in the end effector workspace due to external loads or disturbances.…”

Section: Introductionmentioning

confidence: 85%

“…To expedite training we use the model developed in [6] to train the system on a simulation. The simulation is based on a Cosserat rod formulation [17], with the elasticity and precurvature parameters fit with experimental results [5]. It is important to note that the simulation is used as a data generator for one time data collection and the same could be done on a prototype in an automated manner.…”

Section: A Trainingmentioning

confidence: 99%

“…In this paper, we investigate the control of a unique soft continuum arm known as the BR 2 manipulator [5], [6]. Unlike several other existing soft manipulators, the BR 2 has a completely parallel architecture from an asymmetric combination of soft pneumatic building blocks known as FREEs (Fiber Reinforced Elastomeric Enclosures) that bend and rotate simultaneously, the combination of which yields a spatial deformation pattern as shown in Fig.…”

Section: Introductionmentioning

confidence: 99%

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Open Loop Position Control of Soft Continuum Arm Using Deep Reinforcement Learning

Satheeshbabu

Uppalapati

Chowdhary

et al. 2019

2019 International Conference on Robotics and Automation (ICRA)

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Soft robots undergo large nonlinear spatial deformations due to both inherent actuation and external loading. The physics underlying these deformations is complex, and often requires intricate analytical and numerical models. The complexity of these models may render traditional modelbased control difficult and unsuitable. Model-free methods offer an alternative for analyzing the behavior of such complex systems without the need for elaborate modeling techniques. In this paper, we present a model-free approach for open loop position control of a soft spatial continuum arm, based on deep reinforcement learning. The continuum arm is pneumatically actuated and attains a spatial workspace by a combination of unidirectional bending and bidirectional torsional deformation. We use Deep-Q Learning with experience replay to train the system in simulation. The efficacy and robustness of the control policy obtained from the system is validated both in simulation and on the continuum arm prototype for varying external loading conditions.

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Section: Introductionmentioning

confidence: 85%

Section: A Trainingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Open Loop Position Control of Soft Continuum Arm Using Deep Reinforcement Learning

Satheeshbabu

Uppalapati

Chowdhary

et al. 2019

2019 International Conference on Robotics and Automation (ICRA)

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“…An initial investigation into the aforementioned characterization scheme for a combination of a single bending B and rotating R manipulator was presented in our previous work [27]. In Section III of this paper, we briefly review this characterization scheme, which is now generalized to predict the forward analysis of the BR 2 manipulator.…”

Section: B Approachmentioning

confidence: 99%

“…In Section III of this paper, we briefly review this characterization scheme, which is now generalized to predict the forward analysis of the BR 2 manipulator. The focus of this paper is different from [27], in that it uses the analysis framework for the optimal design of the BR 2 manipulator, and to study its workspace and dexterity metrics. The resulting implications of this paper are significant, as it demonstrates the advantage of BR 2 architecture over existing symmetric architectures through an objective comparison of the workspace and dexterity.…”

Section: B Approachmentioning

confidence: 99%

Design of Soft Continuum Manipulators Using Parallel Asymmetric Combination of Fiber Reinforced Elastomers

Uppalapati¹,

Krishnan²

2018

Preprint

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Soft continuum manipulators have large workspace, dexterity and adaptability, but at the cost of complex design construction highlighted by concatenating several individually controlled serial segments. In this paper, we propose a new designarchitecture for a soft continuum manipulator composed of a parallel combination of pneumatic actuators. The BR2 manipulator, featured in this paper is asymmetric as it combines one soft bending (B) actuator and two soft rotating (R2) actuators, as opposed to state of the art symmetric architectures that adopt bending segments. Spatial deformation modes are achieved by combining curvature and torsion of the individual actuators. This paper formulates a forward analysis method based on Cosserat rod mechanics to predict the spatial deformation of the manipulator under the effect of external loads with an accuracy less than 9 % of the manipulator length. The model takes into account ‘the coupling effect’ inherent to the asymmetric combination, where pressurizing the rotating actuator attenuates the bendingcurvature and vice versa. Consequently, the paper studies the optimal design of the manipulator constituents that minimize the coupling, and thus maximize the workspace and dexterity. A detailed performance study of the BR2 manipulator on aswiveling base demonstrates a spatial workspace quantified by an axisymmetric area, and sufficient dexterity such that at least 87% of the workspace can be approached with two or more orientations. These are validated through obstacle avoidance, and a pick and place task. The manipulator is also capable ofwhole arm manipulation by spiraling along cylindrical objects of varying diameters. These performance attributes surpass any other single segment module and is a potential building block for constructing customized continuum manipulators.

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Analysis of Soft Mechanisms Using a Homogenized Strain Induced Model

Satheeshbabu

Krishnan

2020

Mechanisms and Machine Science

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Parameter estimation and modeling of a pneumatic continuum manipulator with asymmetric building blocks

Cited by 17 publications

References 19 publications

Open Loop Position Control of Soft Continuum Arm Using Deep Reinforcement Learning

Open Loop Position Control of Soft Continuum Arm Using Deep Reinforcement Learning

Design of Soft Continuum Manipulators Using Parallel Asymmetric Combination of Fiber Reinforced Elastomers

Analysis of Soft Mechanisms Using a Homogenized Strain Induced Model

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