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Despite the great diversity of teleoperator designs and applications, their underlying control systems have many similarities. These similarities can be exploited to enable inter-operability between heterogeneous systems. We have developed a network data specification, the Interoperable Telerobotics Protocol, that can be used for Internet based control of a wide range of teleoperators.In this work we test interoperable telerobotics on the global Internet, focusing on the telesurgery application domain. Fourteen globally dispersed telerobotic master and slave systems were connected in thirty trials in one twenty four hour period. Users performed common manipulation tasks to demonstrate effective master-slave operation. With twenty eight (93%) successful, unique connections the results show a high potential for standardizing telerobotic operation. Furthermore, new paradigms for telesurgical operation and training are presented, including a networked surgery trainer and upper-limb exoskeleton control of micro-manipulators.

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In this paper, we focus on robots used for laparoscopic surgery, which is one of the most active areas for research and development of surgical robots. We introduce research and development of laparoscope-holder robots, master-slave robots and hand-held robotic forceps. Then, we discuss future directions for surgical robots. For robot hardware, snake like flexible mechanisms for single-port access surgery (SPA) and NOTES (Natural Orifice Transluminal Endoscopic Surgery) and applications of soft robotics are actively used. On the software side, research such as automation of surgical procedures using machine learning is one of the hot topics.

Pneumatic booster regulators (PBR) are in great demand in modern pneumatic systems for their energy-saving abilities. A new booster regulator with energy recovery (VBA-R) was proposed, and its energy efficiency was investigated by introducing the concept of air power. On the basis of quality-alterable gas thermodynamics, an energy efficiency assessment and pressure response model for VBA-R was proposed. First, a model was solved using MATLAB/Simulink software, and an alternative experiment was designed to verify the mathematical model and performance improvement. The results showed that the simulation was consistent with the experiment. We also can conclude that, first of all, the energy efficiency decreases with the increasing of supply pressure and flow-rate consumption; a VBA-R has the highest efficiency when its diameter ratio is closest to 1.3. Finally, a recovery chamber helped to improve the performance of the VBA-R, which included a boost ratio improvement of 15-25% and an efficiency improvement of 5-10% compared with a conventional VBA booster regulator. This research lays the foundation for optimism regarding the proposed booster regulator.

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Sensing and computing the body states of soft-bodied robots require new methods. Recent studies on soft robotics have shown their feasibility to be applied for these purposes; however, they only addressed solid parts and not the behavior of inner fluids in soft robotics. In this study, we investigated the possibility of a framework that can be used to estimate the body state by exploiting air dynamics in tubes connecting chambers. The framework was designed on the basis of the concept of physical reservoir computing. We focused on a case with a single tube connection. A benchmark task emulated a nonlinear system and was evaluated by simulation. The results showed that the computational ability depended on the inner diameter and length of the tube and can be increased by selecting a suitable diameter and length. We physically implemented the framework for the posture estimation of a soft exoskeleton using pneumatic artificial rubber muscles (PARMs) as the connected chambers and evaluated the accuracy of estimation of a thigh angle. The estimation accuracy showed a similar trend as a function of the tube properties as that observed in the simulation. The framework can exploit the dynamics of air in a tube and may be useful for the state estimation of soft-bodied robots.