Modeling and Reconstruction of State Variables for Low-Level Control of Soft Pneumatic Actuators

To further advance closed-loop control for soft robotics, suitable sensor and modeling strategies have to be investigated. Although there are many flexible and soft sensors available, the integration into the actuator and the use in a control loop is still challenging. Therefore, a state-space model for closed-loop low-level control of a fiber-reinforced actuator using pressure and orientation measurement is investigated. To do so, the integration of an inertial measurement unit and geometric modeling of actuator is presented. The piecewise constant curvature approach is used to describe the actuator’s shape and deformation variables. For low-level control, the chamber’s lengths are reconstructed from bending angles with a geometrical model and the identified material characteristics. For parameter identification and model validation, data from a camera tracking system is analyzed. Then, a closed-loop control of pressure and chambers’ length of the actuator is investigated. It will be shown, that the reconstruction model is suitable for estimating the state variables of the actuator. In addition, the use of the inertial measurement unit will demonstrate a cost-effective and compact sensor for soft pneumatic actuators.

Download Full-text

Local flow sensing on helical microrobots for semi-automatic motion adaptation

The International Journal of Robotics Research ◽

10.1177/0278364919894374 ◽

2019 ◽

Vol 39 (4) ◽

pp. 476-489 ◽

Cited By ~ 4

Author(s):

Antoine Barbot ◽

Dominique Decanini ◽

Gilgueng Hwang

Keyword(s):

Closed Loop ◽

Flow Speed ◽

Closed Loop Control ◽

Flow Profile ◽

Microfluidic Chips ◽

Level Control ◽

Local Flow ◽

Loop Control ◽

Flow Sensing ◽

Swimming Motion

Helical microrobots with dimensions below 100 µm could serve many applications for manipulation and sensing in small, closed environments such as blood vessels or inside microfluidic chips. However, environmental conditions such as surface stiction from the channel wall or local flow can quickly result in the loss of control of the microrobot, especially for untrained users. Therefore, to automatically adapt to changing conditions, we propose an algorithm that switches between a surface-based motion of the microrobot and a 3D swimming motion depending on the local flow value. Indeed swimming is better for avoiding obstacles and difficult surface stiction areas but it is more sensitive to the flow than surface motion such as rolling or spintop motion. First, we prove the flow sensing ability of helical microrobots based on the difference between the tracked and theoretical speed. For this, a 50 µm long and 5 µm diameter helical microrobot measures the flow profile shape in two different microchannels. These measurements are then compared with simulation results. Then, we demonstrate both swimming and surface-based motion using closed-loop control. Finally, we test our algorithm by following a 2D path using closed-loop control, and adapting the type of motion depending on the flow speed measured by the microrobot. Such results could enable simple high-level control that could expand the development of microrobots toward applications in complex microfluidic environments.

Download Full-text

Optimal open-loop/closed-loop control for one-dimensional structures with several state variables

Optimal Control Applications and Methods ◽

10.1002/oca.4660140303 ◽

1993 ◽

Vol 14 (3) ◽

pp. 169-179 ◽

Cited By ~ 4

Author(s):

J. C. Bruch ◽

I. S. Sadek ◽

S. Adali ◽

J. M. Sloss

Keyword(s):

Closed Loop ◽

Open Loop ◽

Closed Loop Control ◽

State Variables ◽

Loop Control ◽

One Dimensional

Download Full-text

Parameter Identification and Closed Loop Control of a Flywheel Mounted Hovering Robot

Volume 4B: Dynamics, Vibration, and Control ◽

10.1115/imece2017-71877 ◽

2017 ◽

Author(s):

Akin Tatoglu

Keyword(s):

Control System ◽

Feedback Control ◽

Transient Response ◽

Closed Loop ◽

Total Error ◽

Acceptable Level ◽

Measurement Unit ◽

Closed Loop Control ◽

Loop Control ◽

Heading Control

A prototype of a hovering multi-terrain mobile robot platform that makes use of a flywheel for stabilization and heading control for rapid maneuverability was developed and presented in a prior paper. It was shown that flywheel stored energy could be transferred to the overall body to generate rapid angular motion once wheel is instantaneously stopped. Solution improved localization accuracy and reduced the overall sensitivity with respect to external disturbances such as non-flat terrain. In this paper, we present a feedback control system to measure dynamic parameters before and after the wheel is stopped. System is designed to follow a predefined path plan and instantaneous torque change causes oscillation after a waypoint is reached. To address this issue, we updated system with an inertial measurement unit (IMU) as a feedback sensor. Then, we investigate the feedback control of individual forward thrust vectors as well as wheel braking timing to minimize amplitude of transient response oscillation and to reduce the steady-state error to an acceptable level that differential drive fans could compensate this error and correct the heading after the rotation around a waypoint occurs. In addition to that, previous mechanical system could transfer all energy stored at once and was not adjustable. In this research, we also investigate varying amount of angular inertia generated by fans and wheel individually and together. To do so, system is modified with stronger forward thrusters. Prior to running the system with a full dynamic model with real mechanism, we implemented a simulation to empirically extract system parameters and adjust controller gains to follow a predefined path with open and closed loop control schemas with objective of minimizing localization error. Finally system is tested with real mechanism. Governing equations, simulation and empirical results comparison are presented and generated trajectories of various simulation and real world settings are listed. Test results verify that, with a closed loop control system, overshoot and total error about a waypoint can be minimized to an acceptable level at and after transient response phase.

Download Full-text

The Impact of Visual Feedback Type on the Mastery of Visuo-Motor Transformations

Zeitschrift für Psychologie ◽

10.1027/2151-2604/a000084 ◽

2012 ◽

Vol 220 (1) ◽

pp. 3-9 ◽

Cited By ~ 4

Author(s):

Sandra Sülzenbrück

Keyword(s):

Empirical Research ◽

Visual Feedback ◽

Closed Loop ◽

Motor Planning ◽

Visual Input ◽

Closed Loop Control ◽

Loop Control ◽

Feedback Type ◽

Effective Use ◽

The Impact

For the effective use of modern tools, the inherent visuo-motor transformation needs to be mastered. The successful adjustment to and learning of these transformations crucially depends on practice conditions, particularly on the type of visual feedback during practice. Here, a review about empirical research exploring the influence of continuous and terminal visual feedback during practice on the mastery of visuo-motor transformations is provided. Two studies investigating the impact of the type of visual feedback on either direction-dependent visuo-motor gains or the complex visuo-motor transformation of a virtual two-sided lever are presented in more detail. The findings of these studies indicate that the continuous availability of visual feedback supports performance when closed-loop control is possible, but impairs performance when visual input is no longer available. Different approaches to explain these performance differences due to the type of visual feedback during practice are considered. For example, these differences could reflect a process of re-optimization of motor planning in a novel environment or represent effects of the specificity of practice. Furthermore, differences in the allocation of attention during movements with terminal and continuous visual feedback could account for the observed differences.

Download Full-text