Ionic electromechanically active polymers (IEAP) are laminar composites that can be considered attractive candidates for soft actuators. Their outstanding properties such as low operating voltage, easy miniaturization, and noiseless operation are, however, marred by issues related to the repeatability in the production and operation of these materials. Implementing closed-loop control for IEAP actuators is a viable option for overcoming these issues. Since IEAP laminates also behave as mechanoelectrical sensors, it is advantageous to combine the actuating and sensing functionalities of a single device to create a so-called self-sensing actuator. This review article systematizes the state of the art in producing self-sensing ionic polymer actuators. The IEAPs discussed in this paper are conducting (or conjugated) polymers actuators (CPA), ionic polymer-metal composite (IPMC), and carbonaceous polymer laminates.

A large-scale effort was carried out to test the performance of seven types of ionic electroactive polymer (IEAP) actuators in space-hazardous environmental factors in laboratory conditions. The results substantiate that the IEAP materials are tolerant to long-term freezing and vacuum environments as well as ionizing Gamma-, X-ray, and UV radiation at the levels corresponding to low Earth orbit (LEO) conditions. The main aim of this material behaviour investigation is to understand and predict device service time for prolonged exposure to space environment.

Electroactive polymers are materials that change their properties (e.g. size and shape) while stimulated by an electric field/current. Conversely, they produce an electrical signal if bent. As both actuators and sensors, they are considered attractive for various applications, e.g. in biomedicine and robotics. Self-sensing actuators made of these materials are still a topic of great interest among researchers. This paper proposes a new self-sensing ionic polymer-metal composite (IPMC) actuating device. By specially patterning the opposite metal electrodes of an IPMC strip, an actuator and a sensor are formed on a single piece of the material. Self-sensitivity is attained by measuring the changing resistance of the sensor part of the structure. This paper introduces the methods for patterning the surface of an IPMC strip and measuring the resistance change during the actuator work cycle, and gives experimental evidence of the suitability of the proposed method for the realization of a smart motion actuator.

In this paper, we present a computationally efficient trajectory optimizer that can exploit GPUs to jointly compute trajectories of tens of agents in under a second. At the heart of our optimizer is a novel reformulation of the nonconvex collision avoidance constraints that reduces the core computation in each iteration to that of solving a large scale, convex, unconstrained Quadratic Program (QP). We also show that the matrix factorization/inverse computation associated with the QP needs to be done only once and can be done offline for a given number of agents. This further simplifies the solution process, effectively reducing it to a problem of evaluating a few matrix-vector products. Moreover, for a large number of agents, this computation can be trivially accelerated on GPUs using existing off-the-shelf libraries. We validate our optimizer's performance on challenging benchmarks and show substantial improvement over state of the art in computation time and trajectory quality.

This paper further discusses a concept of creating a self-sensing ionic polymer-metal composite (IPMC) actuating device with patterned surface electrodes where the actuator and sensor elements are separated by a grounded shielding electrode. Different patterning methods are discussed and compared in detail; the presented experimental data give an understanding of the qualitative properties of the patterns created. Finally, an electromechanical model of the device is proposed and validated.