Scientific research and development on the control of autonomous airship have shown a significant growth in recent years. New applications appear in the areas such as freight carrier, advertising, monitoring, surveillance, transportation, military and scientific research. The control of Autonomous airship is a very important problem for the aerial robots research. In this paper, the previous research on the control of autonomous blimp is reviewed, Several popular control methods are categorized and discussed in detail. Then an intelligent navigation control method, reinforcement learning control, is introduced in the autonomous blimp which was used for 2007 UAV Outback Challenge. The future work on intelligent airship control is also outlined.

This research presents the design, modeling, and control for a bio-inspired robotic hand with antagonistic variable stiffness (AVS). A key design character is the integrated modular finger unit. The modular finger unit is developed based on the variable stiffness actuation principle and has physical impact absorption and stiffness adjustment capabilities to achieve safer grasping and manipulation in interactions and adjustable system bandwidth. Compared with the design of the previous version, the finger unit is optimized in terms of mechanism, cable path, transmission gap, and manufacturing process, and specially designed torque sensors are added to achieve the force perception of the fingertip in three dimensions. A modularized finger unit integrating mechanical parts, sensors, and electronic devices with more compact size, higher precision, and low friction is developed, which eventually lead to the implementation of the fully actuated AVS hand with three fingers and eight degrees of freedom (DOF). The hand controller hardware developed based on a field programmable gate array (FPGA) chip is integrated in the palm. These have guaranteed the real-time and stable grasping and manipulation performance of the hand.

This paper mainly studies the trajectory tracking control problem of the manipulator of TianGong-2 when capturing floating objects in the experimental cabin. Microgravity environment will lead to the existing control system of space robot can not produce good control effect. Different gravity environments change the design requirements of space robots, and the ground test cannot meet these space requirements. In this paper, a fuzzy control strategy based on a spatial extended state observer(FC-SESO) is proposed to solve these inconsistent problems. First, a spatial extended state observer is designed to estimate the influence of disturbance on the system. In order to estimate the disturbance quickly and accurately, a disturbance model including gust is established. Second, in order to ensure the rapid convergence of the desired trajectory, the fuzzy control law is derived. Based on Lyapunov stability theory, the stability of the control system based on the spatial extended state observer is proven. Finally, the proposed system is simulated and captured on the Tiangong-2 manipulator platform to verify the effectiveness of the control algorithm.

This study traces the development of dexterous hand research and proposes a novel antagonistic variable stiffness dexterous finger mechanism to improve the safety of dexterous hand in unpredictable environments, such as unstructured or man-made operational errors through comprehensive consideration of cost, accuracy, manufacturing, and application. Based on the concept of mechanical passive compliance, which is widely implemented in robots for interactions, a finger is dedicated to improving mechanical robustness. The finger mechanism not only achieves passive compliance against physical impacts, but also implements the variable stiffness actuator principle in a compact finger without adding supererogatory actuators. It achieves finger stiffness adjustability according to the biologically inspired stiffness variation principle of discarding some mobilities to adjust stiffness. The mechanical design of the finger and its stiffness adjusting methods are elaborated. The stiffness characteristics of the finger joint and the actuation unit are analyzed. Experimental results of the finger joint stiffness identification and finger impact tests under different finger stiffness presets are provided to verify the validity of the model. Fingers have been experimentally proven to be robust against physical impacts. Moreover, the experimental part verifies that fingers have good power, grasping, and manipulation performance.

This research proposes the design, sensor modeling, and application of the force sensors for an antagonistic variable stiffness (AVS) hand. The AVS hand is a multi-fingered hand designed to achieve in-hand manipulation and also possess physical impact absorption capabilities. The key design feature of the hand is the finger module developed based on the principle of variable stiffness actuation. Combining the structural features, control requirements and low-cost requirements, the finger force sensing is achieved through joint torque sensors instead of expensive multi-axis force/torque (F/T) sensors. From the mechanical design of the AVS hand, it can be observed that the actuations of the finger joints are highly coupled and have a very compact structure, which makes the torque sensor design challenging. This article proposes two types of torque sensor designs, including a strain-based torque (SBT) sensor and a torque sensor for measuring elastic deformation in the series elastic actuator (SEA), which not only simplifies the wiring and electronics of the hand, but also enhances reliability. The linearity and hysteresis of the SBT sensor do not exceed 2.37% and 0.41%, respectively. The linearity and hysteresis of elastic-deformation based torque sensor do not exceed 10.12% and 11.32%, respectively. We validated the effectiveness of the proposed torque sensing method through impedance control.