This paper presents a novel solution for underwater intention recognition that simultaneously detects head motion and throat vibration, enhancing multimodal human-robot interactions for underwater diving. The system pairs with an underwater supernumerary robotic limb (SuperLimb), providing propulsion assistance to reduce the diver’s physical load and mental fatigue. An inertial measurement unit monitors head motion, while a throat microphone captures vocal vibrations. Learning algorithms process these signals to accurately interpret the diver’s intentions and map them to the SuperLimb for posture management. The system features a compact design optimized for diving scenarios and includes a multimodal, real-time classification algorithm to distinguish various head motions and vocal signals. By collecting and analyzing underwater throat vibration data, the study demonstrates the feasibility of this approach, enabling continuous motion commands for enhanced diving assistance. The results show that the head motion recognition component of the system achieved a high classification accuracy of 95%, and throat vibration classification reached 86% accuracy on land and 89% underwater for various purposes.

Planar mechanisms dominate modern designs of legged robots with remote actuator placement for robust agility in ground mobility. This paper presents a novel design of robotic leg modules using the Bennett linkage, driven by two coaxially arranged quasi-direct actuators capable of omnidirectional ground locomotion. The Bennett linkage belongs to a family of overconstrained linkages with three-dimensional spatial motion and unparalleled joint axes. We present the first work regarding the design, modeling, and optimization of the Bennett leg module, enabling lateral locomotion, like the crabs, that was not capable with robotic legs designed with common planar mechanisms. We further explored the concept of overconstrained robots, which is a class of advanced robots based on the design reconfiguration of the Bennett leg modules, serving as a potential direction for future research.

As a potential green electric drive device, the two important green indexes for the systematical design of the switched reluctance machine system with the aim of green, such as the cost of the per unit effective volume output of the system and the systematical efficiency of the machine, are considered. The green-oriented control strategies for the machine system operated in the motor drive, electric traction and generator system, which contribute to increase the systematical efficiency and reduce the cost of the system, are presented. The bases of implementing fault tolerant control strategies are also introduced. Based on the important green indexes and control strategies described two developed prototypes, the electric locomotive switched reluctance motor drive system and variable speed axial-flow fan switched reluctance motor drive system, are given.