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

2024-04-14

International Conference on Soft Robotics

AI Summary

Large-scale pneumatic soft robots lack scalable, high-precision real-time pressure control systems and dynamic modeling tools suitable for real-time control. Method: This paper introduces PneuDrive—a modular embedded pressure control system—and the first real-time-control-oriented tri-model dynamic modeling toolkit. PneuDrive features a novel scalable RS-485 bus architecture enabling multi-node daisy-chaining, closed-loop control of 16 valves (0–100 psig), and reliable communication over distances exceeding 10 meters. The modeling toolkit integrates data-driven, physics-based, and hybrid models, supporting hysteresis compensation, fluid–structure interaction modeling, and quantitative performance benchmarking. Contribution/Results: Evaluated on a three-segment continuum robot, the system achieves coordinated trajectory tracking across 12 actuation channels. All three model types are experimentally calibrated and validated via real-time simulation, establishing both a hardware platform and a modeling paradigm for real-time control of pneumatic soft robots.

Technology Category

• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Planning, Routing, and Scheduling: Model-Based Reasoning
• Machine Learning: Hardware-aware ML

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

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.

Problem

• Develops modular pressure control for large-scale soft robots
• Enables distributed pressure control with high flow rates
• Provides modeling toolkit for real-time simulation and control

Innovation

• Modular pressure control for large soft robots
• Daisy-chained RS-485 bus for distributed control
• Python API and ROS node for flexible integration