This paper presents a systematical approach to develop a novel reduced complexity quadruped (RCQ) robot designed for serpentine robotic tail research purposes. The critical design requirements are determined based on careful dynamic analysis and synthesis results. Guided by formulated design requirements and principles, a robot prototype was designed and built. The robot has an overall weight of 5 Kg and the body size of a domestic cat. The existing electronic system allows a control frequency of up to 1 kHz and accepts both torque and position commands. These features guarantee that the platform could be used to explore the dynamic usages of robotic tails on legged locomotion. The preliminary tests show that the hardware can lift itself off the ground up to 112 mm (46.7% of its body height) and stay in the air for at least 0.3 seconds.

This paper presents the design and development of a novel, low-profile, exoskeleton robotic glove aimed for people who suffer from brachial plexus injuries to restore their lost grasping functionality. The key idea of this new glove lies in its new finger mechanism that takes advantage of the rigid coupling hybrid mechanism (RCHM) concept. This mechanism concept couples the motions of the adjacent human finger links using rigid coupling mechanisms so that the overall mechanism motion (e.g., bending, extension, etc.) could be achieved using fewer actuators. The finger mechanism utilizes the single degree of freedom case of the RCHM that uses a rack-and-pinion mechanism as the rigid coupling mechanism. This special arrangement enables to design each finger mechanism of the glove as thin as possible while maintaining mechanical robustness simultaneously. Based on this novel finger mechanism, a two-finger low-profile robotic glove was developed. Remote center of motion mechanisms were used for the metacarpophalangeal (MCP) joints. Kinematic analysis and optimization-based kinematic synthesis were conducted to determine the design parameters of the new glove. Passive abduction/adduction joints were considered to improve the grasping flexibility. A proof-of-concept prototype was built and pinch grasping experiments of various objects were conducted. The results validated the mechanism and the mechanical design of the new robotic glove and demonstrated its functionalities and capabilities in grasping objects with various shapes and weights that are used in activities of daily living (ADLs).

Vehicular edge computing (VEC) offers a new paradigm to improve vehicular services and augment the capabilities of vehicles. In this article, we study the problem of task scheduling in VEC, where multiple computation-intensive vehicular applications can be offloaded to roadside units (RSUs) and each application can be further divided into multiple tasks with task dependency. The tasks can be scheduled to different mobile-edge computing servers on RSUs for execution to minimize the average completion time of multiple applications. Considering the completion time constraint of each application and the processing dependency of multiple tasks belonging to the same application, we formulate the multiple tasks scheduling problem as an optimization problem that is NP-hard. To solve the optimization problem, we develop an efficient task scheduling algorithm. The basic idea is to prioritize multiple applications and prioritize multiple tasks so as to guarantee the completion time constraints of applications and the processing dependency requirements of tasks. The numerical results demonstrate that our proposed algorithm can significantly reduce the average completion time of multiple applications compared with benchmark algorithms.

Mobile Edge Computing (MEC) offers a new paradigm to improve vehicular services and augment the capabilities of vehicles. In this paper, to reduce the latency of the computation offloading of vehicles, we study multiple vehicles computation offloading problem in vehicular edge networks. We formulate the problem as a multi-user computation offloading game problem, prove the existence of Nash equilibrium (NE) of the game and propose a distributed computation offloading algorithm to compute the equilibrium. We analyze the price of anarchy of the game algorithm and evaluate the performance of the game algorithm using extensive simulations. Numerical results show that the proposed algorithm can greatly reduce the computation overhead of vehicles.