Biocompatible Electromagnetic Soft Actuator Network: Design Optimization, Development, Fabrication and Test
The design of robots that are light, soft, and powerful is a grand challenge. Since they can easily adapt to dynamic environments, soft robotic systems have the potential of changing the status-quo of bulky robotics. A crucial component of soft robotics is a soft actuator that is activated by external stimuli to generate desired motions. Unfortunately, there is a lack of powerful soft actuators that operate through lightweight power sources. To that end, we recently designed a highly scalable, flexible, biocompatible Electromagnetic Soft Actuator (ESA). Artificial muscles can be developed by integrating a network of ESAs. The main research gap addressed in this work is in the absence of system-theoretic understanding of the impact of the real-time control and actuator selection algorithms on the performance of networked soft-body actuators and ESAs. The objective of this research is to establish a framework that guides the analysis and robust control of networked ESAs. A novel ESA is described, and a configuration of soft actuator matrix to resemble artificial muscle fiber is presented. A mathematical model which depicts the physical network is derived, considering the disturbances due to external forces and linearization errors as an integral part of this model. Then, a robust control and minimal actuator selection problem with logistic constraints and control input bounds is formulated, and tractable computational routines are proposed with numerical case studies. This research also discusses the design optimization of an electromagnetic soft actuator composed of two antagonistic solenoids that share a permanent magnet core. First, calculation of the magnetic field and applied force of a solenoid with a permanent magnet plunger is presented as the principal component of this electromagnetic actuator. Design optimization of the coil is discussed considering the geometrical parameters of the coil, including its length, inner and average diameters, number of turns, and packing density while the power consumption is bounded. The impact of the actuator size on the resultant force is presented and scaling limitations are discussed. Then, due to the soft nature of the actuator's component, the impact of the cross-section, i.e. lateral deformation of the actuator on the magnetic field at the center of the section is investigated as well. The deformation might happen to the actuator due to the load in the transverse direction, especially when the actuator is made of flexible materials. This research also presents a design optimization framework based on Branch and Bound Algorithm for the network of novel electromagnetic soft actuators. The soft actuators work based on the operating principle of solenoids but are made of intrinsically soft materials. We confirmed that by scaling down the size of the soft actuators, their force to volume ratio increases. This suggests that by miniaturizing the size of the actuator and attaching them as a network based on the arrangement of actin and myosin filaments in skeletal muscles, the output force can be enhanced. In order to achieve the maximum output force, design parameters of a single soft actuator, as well as those of a network, are considered as design variables. The maximum available volume (thickness, width, and length) and deflection range of the network are considered design constraints. The cost function, i.e. the output force, is a non-linear mixed-integer function. A Branch and Bound optimization algorithm based on interval analysis is then proposed to solve the optimization problem. Numerical simulations are presented for a representative example of an active soft brace for the human elbow joint. The results suggest that an electromagnetic soft actuator network can provide sufficient torque to be used as a drive train for an active elbow brace for both flexion and extension over a range of around 93 degrees.