Design, Manufacturing and Open-Loop Control of a Soft Pneumatic Arm: Conclusions

Table of Links

Abstract and 1 Introduction

2 Related Works

2.1 Pneumatic Actuation

2.2 Pneumatic Arms

2.3 Control of Soft Robots

3 PAUL: Design and Manufacturing

3.1 Robot Design

3.2 Material Selection

3.3 Manufacturing

3.4 Actuation Bank

4 Data Acquisition and Open-Loop Control

4.1 Hardware Setup

4.2 Vision Capture System

4.3 Dataset Generation: Table-Based Models

4.4 Open-Loop Control

5 Results

5.1 Final PAUL version

5.2 Workspace Analysis

5.3 Performance of the Table-Based Models

5.4 Bending Experiments

5.5 Weight Carrying Experiments

6 Conclusions

Funding Information

A. Conducted Experiments and References

6 Conclusions

The numerous advantages and wide range of potential applications that soft robotics presents have made it a priority field of research in recent years. The difficulty, however, still present when it comes to both building and manufacturing robots, makes it a very incipient discipline. In the field of pneumatic robots, examples of existing manipulator arms are scarce, although cable and SMAs-based manipulators do exist.

In this work, PAUL has been presented, a modular robotic arm, made of silicone and that uses PLA for the joints between segments. Each module is made up of three bladders, which provide it with 3 degrees of freedom, which are reduced to 2 in the control in order to reduce redundancies. The actuation of the segments is done by sending different inflation times to each valve. The Pneunet type structure in the bladders allows the entire module to curve, reaching different positions in space.

The final implementation presented here has 3 segments and has had to address, first of all, an adequate design, which has been adjusted iteratively, and a correct selection of materials. Specifically, we have chosen a silicone that is slow enough to minimise bubbles, the main source of breakage and subsequent leaks, and at the same time, with sufficient hardness and density to avoid a high weight of the assembly. In addition to this, the pneumatic bench and the electronics in charge of controlling it had to be sized and designed.

PAUL has been modelled on open chain. To this end, a vision system has been designed, first of all, in charge of extracting, from the capture of a beacon, the position and orientation of the final end of the robot. Subsequently, an automated data collection process has been established that has allowed the generation of a dataset large enough to model, based on triangulations, both the direct and inverse kinematics of the system.

Specifically, accuracies of 4 mm have been obtained for direct kinematics and 11 mm in the best points for inverse kinematics, in line with existing results in the literature for manipulators with similar lengths (40 cm). In addition to this, the experiments have also demonstrated the enormous flexibility and bending capacity of PAUL as well as its ability to carry loads without increasing its positioning error, which reaffirms the ability of soft robotics to adapt to numerous applications.

Concretely, two applications have been considered where PAUL could have a very good fit. On the one hand, the inspection of pipes or unstructured environments with difficult access and twisted geometries. This is an application in which the position errors found here are negligible compared to the diameter of a pipe and in which, if necessary, the robot could be controlled by direct inflation of the bladders –making use of direct kinematics– since the aim is not to place PAUL at a certain point but to progressively sweep a region.

Its high modularity and its great capacity for adding segments make it possible to adapt to any type of environment to explore. Furthermore, given that it can carry small weights, the addition of a light camera (there are webcams weighing less than 100 g) would not represent any additional error. Although the bending capacity of this manipulator is not the highest, the concatenation of bends in the different successive ones should be enough to adapt the shape of the pipe.

On the other hand, PAUL could be a useful aid in collaborative manipulation of light objects with humans. In various daily activities –such as a warehouse, a pharmacy or a fast food establishment– the last part of the product delivery process consists of picking it up from a table and sorting it into drawers or rails. These are very light objects that are placed in spaces several centimetres wide. For optimisation reasons, many times the region where the products are classified is very high, that is, it would require a robot with bending capabilities of some importance.

Although there have been completely robotic solutions for years, due to the danger associated with rigid manipulators, these prevent workers from entering these areas. The use of soft robots, however, would allow collaborative work in them and reduce total costs, opening the door to automation for many small companies.

Great developments are therefore still expected in the coming years. Closed chain control, the use of more sophisticated modelling techniques and the management of inverse kinematics could be the contributions that PAUL would continue to make in this field in the near future.

Funding Information

Work result of research activities carried out at the Centre for Automation and Robotics, CAR (UPM-CSIC), within the Robotics and Cybernetics research group (RobCib). Supported by the “Ayudas para contratos predoctorales para la realizaci´on del doctorado con menci´on internacional en sus escuelas, facultad, centros e institutos de I+D+i”, funded by Programa Propio I+D+i 2022 from Universidad Polit´ecnica de Madrid”, by the TASAR (Team of Advanced Search And Rescue Robots)”, funded by “Proyectos de I+D+i del Ministerio de Ciencia, Innovacion y Universidades” (PID2019- 105808RB-I00), by the “RoboCity2030-DIH-CM, Madrid Robotics Digital Innovation Hub”, S2018/NMT-4331, funded by “Programas de Actividades I+D en la Comunidad Madrid” and co-funded by Structural Funds of the EU, and by the “Proyecto CollaborativE Search And Rescue robots (CESAR)” (PID2022-142129OB-I00) funded by MCIN/AEI/10.13039/501100011033 and “ERDF A way of making Europe”

A Conducted Experiments

A video presenting validating the inverse kinematic model and PAUL’s bending ability can be consulted in the following link: https://drive.upm.es/s/iIU6sGbisTkrwWa

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