Controlling Soft Robots: Balancing Feedback and Feedforward Elements

Abstract

Soft robots (SRs) represent one of the most significant recent evolutions in robotics. Designed to embody safe and natural behaviors, they rely on compliant physical structures purposefully designed to embody desirable and sometimes variable impedance characteristics. This article discusses the problem of controlling SRs. We start by observing that most of the standard methods of robotic control-e.g., high-gain robust control, feedback linearization, backstepping, and active impedance control-effectively fight against or even completely cancel the physical dynamics of the system, replacing them with a desired model. This defeats the purpose of introducing physical compliance. After all, what is the point of building soft actuators if we then make them stiff by control

Dynamic control of soft robots interacting with the environment

“…In this way the natural softness of the robot is preserved during possible interactions with an external environment. Please refer to [29] for more details on this. The integral action is included for compensating the mismatches between the real system and the approximated model considered here.…”

Modeling Previous Trial Effect in Human Manipulation through Iterative Learning Control

“…In ref. [29] we observed that such rule can be seen in the more general theory of Iterative Learning Control (ILC). [22] Indeed, ILC exploits the error evolution in the whole interval ½t 0 , t f Þ of a previous iteration, to update a feedforward command, according to the law…”

Soft Robotics: A Review of Recent Developments of Pneumatic Soft Actuators

“…To answer this issue, an algorithm called Iterative Learning Control (ILC) was developed. When the ILC algorithm was used with a low stiffness robot, the robot was able to recognize an object in the environment and stop its own motion before moving the object [58]. There is also a control system known as a Proportional-Integral-Derivative (PID) controller, which is a control loop mechanism that utilizes feedback to keep a constant variable.…”

“…One of the biggest issues in the field of soft robotics is finding methods and models which are both accurate to experimental values and computationally viable [48,[112][113][114][115][116][117]. Due to the deformable nature of under-actuated soft robotics, they are dynamically formulated using a system of infinite dimensions [23,58,93,[118][119][120]. These designs are currently unable to be reduced to an exact model which often leads to rigid-body assumptions to create manageable dynamic equations [121].…”