Soft robots have the appealing advantages of being highly flexible and adaptive to complex environments. However, the low‐stiffness nature of the constituent materials makes soft robotic systems incompetent in tasks requiring relatively high load capacity. Despite recent attempts to develop stiffness‐tunable soft actuators by employing variable stiffness materials and structures, the reported stiffness‐tunable actuators generally suffer from limitations including slow responses, small deformations, and difficulties in fabrication with microfeatures. This work presents a paradigm to design and manufacture fast‐response, stiffness‐tunable (FRST) soft actuators via hybrid multimaterial 3D printing. The integration of a shape memory polymer layer into the fully printed actuator body enhances its stiffness by up to 120 times without sacrificing flexibility and adaptivity. The printed Joule‐heating circuit and fluidic cooling microchannel enable fast heating and cooling rates and allow the FRST actuator to complete a softening–stiffening cycle within 32 s. Numerical simulations are used to optimize the load capacity and thermal rates. The high load capacity and shape adaptivity of the FRST actuator are finally demonstrated by a robotic gripper with three FRST actuators that can grasp and lift objects with arbitrary shapes and various weights spanning from less than 10 g to up to 1.5 kg.
Locomotion mode identification is essential for the control of a robotic rehabilitation exoskeletons. This paper proposes an online support vector machine (SVM) optimized by particle swarm optimization (PSO) to identify different locomotion modes to realize a smooth and automatic locomotion transition. A PSO algorithm is used to obtain the optimal parameters of SVM for a better overall performance. Signals measured by the foot pressure sensors integrated in the insoles of wearable shoes and the MEMS-based attitude and heading reference systems (AHRS) attached on the shoes and shanks of leg segments are fused together as the input information of SVM. Based on the chosen window whose size is 200 ms (with sampling frequency of 40 Hz), a three-layer wavelet packet analysis (WPA) is used for feature extraction, after which, the kernel principal component analysis (kPCA) is utilized to reduce the dimension of the feature set to reduce computation cost of the SVM. Since the signals are from two types of different sensors, the normalization is conducted to scale the input into the interval of [0, 1]. Five-fold cross validation is adapted to train the classifier, which prevents the classifier over-fitting. Based on the SVM model obtained offline in MATLAB, an online SVM algorithm is constructed for locomotion mode identification. Experiments are performed for different locomotion modes and experimental results show the effectiveness of the proposed algorithm with an accuracy of 96.00% ± 2.45%. To improve its accuracy, majority vote algorithm (MVA) is used for post-processing, with which the identification accuracy is better than 98.35% ± 1.65%. The proposed algorithm can be extended and employed in the field of robotic rehabilitation and assistance.
Rescue missions after coal mine accidents are highly risky and sometimes impossible for rescuers to perform. To decrease the risk to rescuers, two generations of tracked mobile robots have been designed and developed to replace the rescuers. In this paper, we present the design iterations with experiments carried out in training sites for rescuers and in working coal mines, and we summarize the design and development experiences of the mobile robots for such rescue missions. In coal mine rescue robots, the explosion‐proof and waterproof designs are adapted to the explosive and wet environments, while the suspension systems are adapted to the unstructured working environments. The design and development experiences may provide a reference for designing and developing future mobile robot systems for coal mine accident rescue missions.
The CO-releasing materials (CORMats) are used as substances for producing CO molecules for therapeutic purposes. Carbon monoxide (CO) imparts toxic effects to biological organisms at higher concentration. If this characteristic is utilized in a controlled manner, it can act as a cell-signaling agent for important pathological and pharmacokinetic functions; hence offering many new applications and treatments. Recently, research on therapeutic applications using the CO treatment has gained much attention due to its nontoxic nature, and its injection into the human body using several conjugate systems. Mainly, there are two types of CO insertion techniques into the human body, i.e., direct and indirect CO insertion. Indirect CO insertion offers an advantage of avoiding toxicity as compared to direct CO insertion. For the indirect CO inhalation method, developers are facing certain problems, such as its inability to achieve the specific cellular targets and how to control the dosage of CO. To address these issues, researchers have adopted alternative strategies regarded as CO-releasing molecules (CORMs). CO is covalently attached with metal carbonyl complexes (MCCs), which generate various CORMs such as CORM-1, CORM-2, CORM-3, ALF492, CORM-A1 and ALF186. When these molecules are inserted into the human body, CO is released from these compounds at a controlled rate under certain conditions or/and triggers. Such reactions are helpful in achieving cellular level targets with a controlled release of the CO amount. However on the other hand, CORMs also produce a metal residue (termed as i-CORMs) upon degradation that can initiate harmful toxic activity inside the body. To improve the performance of the CO precursor with the restricted development of i-CORMs, several new CORMats have been developed such as micellization, peptide, vitamins, MOFs, polymerization, nanoparticles, protein, metallodendrimer, nanosheet and nanodiamond, etc. In this review article, we shall describe modern ways of CO administration; focusing primarily on exclusive features of CORM’s tissue accumulations and their toxicities. This report also elaborates on the kinetic profile of the CO gas. The comprehension of developmental phases of CORMats shall be useful for exploring the ideal CO therapeutic drugs in the future of medical sciences.
In this paper, a control strategy is proposed to improve the tracking performance of the lower limb exoskeleton (LLE). The proposed active disturbance rejection control (ADRC) with fast terminal sliding mode control (FTSMC) can not only alleviate the disturbance but also converge to a bounded region fast. Based on the robotics analysis, a dynamic model for the LLE was established. To achieve decoupling control for a coupled system, the virtual control input was introduced, where the system uncertainty and external disturbances were regarded as lumped disturbances. To validate the feasibility of the proposed control strategy, the simulations and experiments were both carried out. The numerical simulation results were shown that the proposed control strategy and ADRC can remarkably reduce the chattering phenomena, which is owing to the estimation ability of extended state observer (ESO). Both the simulations and the experiments results were shown that this strategy was better than the conventional proportional-integralderivative (PID) and ADRC in terms of tracking performance. With the proposed ADRC-FTSMC, the LLE system can achieve higher tracking precision and faster response.INDEX TERMS Lower limb exoskeleton, active disturbance rejection, fast terminal sliding mode control, human gait tracking, finite-time convergence.
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