Table of Contents
Fetching ...

PneuDrive: An Embedded Pressure Control System and Modeling Toolkit for Large-Scale Soft Robots

Curtis C. Johnson, Daniel G. Cheney, Dallin L. Cordon, Marc D. Killpack

TL;DR

To enable meter-scale soft robots, the authors introduce PneuDrive, a modular RS-485-based pressure-control system with embedded boards that support distributed, closed-loop control for many valves and high flow. The approach is complemented by a modeling toolkit offering three dynamic actuation models—linear, nonlinear, and parametric—along with Python-based parameter identification to support real-time simulation and control. Hardware demonstrations on a 1.16 m, 3-joint soft arm with 12 chambers show distributed control across multiple devices, achieving high loop rates and robust step/trajectory tracking. The work provides a principled framework for model selection and control design in large-scale soft robotics and releases open-source designs to accelerate research and development in this area.

Abstract

In this paper, we present a modular pressure control system called PneuDrive that can be used for large-scale, pneumatically-actuated soft robots. The design is particularly suited for situations which require distributed pressure control and high flow rates. Up to four embedded pressure control modules can be daisy-chained together as peripherals on a robust RS-485 bus, enabling closed-loop control of up to 16 valves with pressures ranging from 0-100 psig (0-689 kPa) over distances of more than 10 meters. The system is configured as a C++ ROS node by default. However, independent of ROS, we provide a Python interface with a scripting API for added flexibility. We demonstrate our implementation of PneuDrive through various trajectory tracking experiments for a three-joint, continuum soft robot with 12 different pressure inputs. Finally, we present a modeling toolkit with implementations of three dynamic actuation models, all suitable for real-time simulation and control. We demonstrate the use of this toolkit in customizing each model with real-world data and evaluating the performance of each model. The results serve as a reference guide for choosing between several actuation models in a principled manner. A video summarizing our results can be found here: https://bit.ly/3QkrEqO.

PneuDrive: An Embedded Pressure Control System and Modeling Toolkit for Large-Scale Soft Robots

TL;DR

To enable meter-scale soft robots, the authors introduce PneuDrive, a modular RS-485-based pressure-control system with embedded boards that support distributed, closed-loop control for many valves and high flow. The approach is complemented by a modeling toolkit offering three dynamic actuation models—linear, nonlinear, and parametric—along with Python-based parameter identification to support real-time simulation and control. Hardware demonstrations on a 1.16 m, 3-joint soft arm with 12 chambers show distributed control across multiple devices, achieving high loop rates and robust step/trajectory tracking. The work provides a principled framework for model selection and control design in large-scale soft robotics and releases open-source designs to accelerate research and development in this area.

Abstract

In this paper, we present a modular pressure control system called PneuDrive that can be used for large-scale, pneumatically-actuated soft robots. The design is particularly suited for situations which require distributed pressure control and high flow rates. Up to four embedded pressure control modules can be daisy-chained together as peripherals on a robust RS-485 bus, enabling closed-loop control of up to 16 valves with pressures ranging from 0-100 psig (0-689 kPa) over distances of more than 10 meters. The system is configured as a C++ ROS node by default. However, independent of ROS, we provide a Python interface with a scripting API for added flexibility. We demonstrate our implementation of PneuDrive through various trajectory tracking experiments for a three-joint, continuum soft robot with 12 different pressure inputs. Finally, we present a modeling toolkit with implementations of three dynamic actuation models, all suitable for real-time simulation and control. We demonstrate the use of this toolkit in customizing each model with real-world data and evaluating the performance of each model. The results serve as a reference guide for choosing between several actuation models in a principled manner. A video summarizing our results can be found here: https://bit.ly/3QkrEqO.

Paper Structure

This paper contains 16 sections, 12 equations, 9 figures, 2 tables.

Figures (9)

  • Figure 1: PneuDrive Controller (left) and PneuDrive Embedded (right) boards.
  • Figure 2: Two modules connected on a single RS485 bus for distributed embedded control of large-scale soft robots. Each board is powered from a common power bus (10-28V DC) for closed-loop control of up to 4 valve/chamber pairs. The dashed lines indicate that the bus can extend over large physical distances.
  • Figure 3: Onboard functionality of PneuDrive Embedded board.
  • Figure 4: Communication Protocol for PneuDrive. Each data frame uses the '8N1' serial setting for a total of 10 bits per data frame. Each 16-bit integer requires two frames, for a total of 10 data frames per packet.
  • Figure 5: Functional diagram demonstrating the physical meaning of important variables in the pressure dynamic models for a pressure chamber of variable volume.
  • ...and 4 more figures