Physics-Informed Modeling and Control of Multi-Actuator Soft Catheter Robots

Catheter-based endovascular interventional procedures have become increasingly popular in recent years as they are less invasive and patients spend less time in the hospital with less recovery time and less pain. These advantages have led to a significant growth in the number of procedures that are performed annually. However, it is still challenging to position a catheter in a target vessel branch within the highly complicated and delicate vascular structure. In fact, vessel tortuosity and angulation, which cause difficulties in catheterization and reaching the target site, have been reported as the main causes of failure in endovascular procedures. Maneuverability of a catheter for intravascular navigation is a key to reaching the target area; ability of a catheter to move within the target vessel during trajectory tracking thus affects to a great extent the length and success of the procedure. To address this issue, this paper models soft catheter robots with multiple actuators and provides a time-dependent model for characterizing the dynamics of multi-actuator soft catheter robots. Built on this model, an efficient and scalable optimization-based framework is developed for guiding the catheter to pass through arteries and reach the target where an aneurysm is located. The proposed framework models the deflection of the multi-actuator soft catheter robot and develops a control strategy for movement of catheter along a desired trajectory. This provides a simulation-based framework for selection of catheters prior to endovascular catheterization procedures, assuring that given a fixed design, the catheter is able to reach the target location. The results demonstrate the benefits that can be achieved by design and control of catheters with multiple number of actuators for navigation into small vessels.

Energy Management Strategy for Hybrid Multimode Powertrains: Influence of Inertial Properties and Road Inclination

Multimode hybrid powertrains have captured the attention of automotive OEMs for their flexible nature and ability to provide better and optimized efficiency levels. However, the presence of multiple actuators, with different efficiency and dynamic characteristics, increases the problem complexity for minimizing the overall power losses in each powertrain operating condition. The paper aims at providing a methodology to select the powertrain mode and set the reference torques and angular speeds for each actuator, based on the power-weighted efficiency concept. The power-weighted efficiency is formulated to normalize the efficiency contribution from each power source and to include the inertial properties of the powertrain components as well as the vehicle motion resistance forces. The approach, valid for a wide category of multimode powertrain architectures, is then applied to the specific case of a two-mode hybrid system where the engagement of one of the two clutches enables an Input Split or Compound Split operative mode. The simulation results obtained with the procedure prove to be promising in avoiding excessive accelerations, drift of powertrain components, and in managing the power flow for uphill and downhill vehicle conditions.

Model Predictive Control-Based Integrated Path Tracking and Velocity Control for Autonomous Vehicle with Four-Wheel Independent Steering and Driving

This paper presents an MPC-based integrated control algorithm for an autonomous vehicle equipped with four-wheel independent steering and driving systems. The objective of this research is to improve the performance of the path and velocity tracking controllers by distributing the control effort to the multiple actuators. The proposed algorithm has two modules: reference state decision and MPC-based vehicle motion controller. Reference state decision module determines reference state profiles consisting of yaw rate and velocity in order to overcome the limitation of the error dynamics-based path tracking controller, which requires several assumptions on the reference path. The MPC-based vehicle motion controller is designed with a linear time-varying vehicle model in order to optimally allocate the control effort to each actuator. A linear time-varying MPC is adopted to reduce computational burden caused by using a non-linear one. The effectiveness of the proposed algorithm is validated via simulation on MATLAB/Simulink and CarSim. The simulation results show that the proposed algorithm improves the reference tracking performance by effectively distributing the control effort to the steering angle and driving force of each actuator.

A dynamic electrically driven soft valve for control of soft hydraulic actuators

Regulation systems for fluid-driven soft robots predominantly consist of inflexible and bulky components. These rigid structures considerably limit the adaptability and mobility of these robots. Soft valves in various forms for fluidic actuators have been developed, primarily fluidically or electrically driven. However, fluidic soft valves require external pressure sources that limit robot locomotion. State-of-the-art electrostatic valves are unable to modulate pressure beyond 3.5 kPa with a sufficient flow rate (>6 mL⋅min−1). In this work, we present an electrically powered soft valve for hydraulic actuators with mesoscale channels based on a different class of ultrahigh-power density dynamic dielectric elastomer actuators. The dynamic dielectric elastomer actuators (DEAs) are actuated at 500 Hz or above. These DEAs generate 300% higher blocked force compared with the dynamic DEAs in previous works and their loaded power density reaches 290 W⋅kg−1 at operating conditions. The soft valves are developed with compact (7 mm tall) and lightweight (0.35 g) dynamic DEAs, and they allow effective control of up to 51 kPa of pressure and a 40 mL⋅min−1 flow rate with a response time less than 0.1 s. The valves can also tune flow rates based on their driving voltages. Using the DEA soft valves, we demonstrate control of hydraulic actuators of different volumes and achieve independent control of multiple actuators powered by a single pressure source. This compact and lightweight DEA valve is capable of unprecedented electrical control of hydraulic actuators, showing the potential for future onboard motion control of soft fluid-driven robots.

Hardware Methods for Onboard Control of Fluidically Actuated Soft Robots

Soft robots provide significant advantages over their rigid counterparts. These compliant, dexterous devices can navigate delicate environments with ease without damage to themselves or their surroundings. With many degrees of freedom, a single soft robotic actuator can achieve configurations that would be very challenging to obtain when using a rigid linkage. Because of these qualities, soft robots are well suited for human interaction. While there are many types of soft robot actuation, the most common type is fluidic actuation, where a pressurized fluid is used to inflate the device, causing bending or some other deformation. This affords advantages with regards to size, ease of manufacturing, and power delivery, but can pose issues when it comes to controlling the robot. Any device capable of complex tasks such as navigation requires multiple actuators working together. Traditionally, these have each required their own mechanism outside of the robot to control the pressure within. Beyond the limitations on autonomy that such a benchtop controller induces, the tether of tubing connecting the robot to its controller can increase stiffness, reduce reaction speed, and hinder miniaturization. Recently, a variety of techniques have been used to integrate control hardware into soft fluidic robots. These methods are varied and draw from disciplines including microfluidics, digital logic, and material science. In this review paper, we discuss the state of the art of onboard control hardware for soft fluidic robots with an emphasis on novel valve designs, including an overview of the prevailing techniques, how they differ, and how they compare to each other. We also define metrics to guide our comparison and discussion. Since the uses for soft robots can be so varied, the control system for one robot may very likely be inappropriate for use in another. We therefore wish to give an appreciation for the breadth of options available to soft roboticists today.

A Nonsmooth Quasistatic Modeling Approach for Hydraulic Actuators

This paper presents an analytical approach for modeling the quasistatic characteristics of hydraulic actuators driven by four-valve independent metering circuits. The presented model is described as a nonsmooth, set-valued function from the velocity to the set of forces with which the equilibrium is achieved at the velocity. It is derived from algebraic relations among the velocity of the actuator, the steady-state force generated by the actuator, and the flowrate and the steady-state pressure at all valves in the circuit. This approach is also applied to more involving circuits including a regeneration pipeline and those with multiple actuators. The contribution of the paper can be seen as an example case study of the fact that these complicated circuit structures are analytically tractable through an extension of the conventional hydraulic-electric analogy. The obtained analytical expressions of the steady-state velocity-force relations allow for concise visualization of the actuators' characteristics.

A pneumatic random-access memory for controlling soft robots

Pneumatically-actuated soft robots have advantages over traditional rigid robots in many applications. In particular, their flexible bodies and gentle air-powered movements make them more suitable for use around humans and other objects that could be injured or damaged by traditional robots. However, existing systems for controlling soft robots currently require dedicated electromechanical hardware (usually solenoid valves) to maintain the actuation state (expanded or contracted) of each independent actuator. When combined with power, computation, and sensing components, this control hardware adds considerable cost, size, and power demands to the robot, thereby limiting the feasibility of soft robots in many important application areas. In this work, we introduce a pneumatic memory that uses air (not electricity) to set and maintain the states of large numbers of soft robotic actuators without dedicated electromechanical hardware. These pneumatic logic circuits use normally-closed microfluidic valves as transistor-like elements; this enables our circuits to support more complex computational functions than those built from normally-open valves. We demonstrate an eight-bit nonvolatile random-access pneumatic memory (RAM) that can maintain the states of multiple actuators, control both individual actuators and multiple actuators simultaneously using a pneumatic version of time division multiplexing (TDM), and set actuators to any intermediate position using a pneumatic version of analog-to-digital conversion. We perform proof-of-concept experimental testing of our pneumatic RAM by using it to control soft robotic hands playing individual notes, chords, and songs on a piano keyboard. By dramatically reducing the amount of hardware required to control multiple independent actuators in pneumatic soft robots, our pneumatic RAM can accelerate the spread of soft robotic technologies to a wide range of important application areas.

Wireless Multiplexing Control Based on Magnetic Coupling Resonance and its Applications in Robot

Nowadays, more and more researchers are pursuing miniaturized and lightweight structure of robots, However, robots with multiple actuators require large control systems if each actuator needs to be controlled independently. In addition, the cables and circuits for control and power supply are the obstacles in reducing size and weight. In this paper, a wireless multiplexing control system based on magnetic coupling resonance (MCR) is proposed. The control system can realize wireless energy transmission and control simultaneously. By decomposing a composite signal, it can control multiple actuators with only one input signal. However, in previous researches, their applications are primary and simple due to the switch control without feedback and the lack of systematic design method for robot application. Thus, based on the discrete form of composite signal, the closed-loop of wireless multiplexing control is presented, which makes this promising method a step closer to the practical application. Besides, based on the theoretical model of load power and transmission efficiency, 5 parameters to be optimized are extracted in accordance with the actual design requirements. The optimization algorithm for load power is proposed using particle swarm optimization (PSO). As for its applications in robots, a Delta robot with flexible linkage and an untethered multi-drive pipe robot for sampling operation are designed to demonstrate the proposed control method. The experiment results of the Delta robot show the reliability and accuracy of the system while the results of the pipe robot prove its potential use in the untethered robot system.