This paper studies the problem of trajectory tracking control for robotic manipulators subject to model uncertainties, external disturbance and actuator saturation. At first, a nonsingular fixed-time sliding mode variable is developed based on a novel fixed-time stable system, which solves the singularity problem brought by the terminal sliding mode control and obtains a fast convergence rate. After that, a novel fixed-time sliding mode observer is designed to estimate and compensate the model uncertainties and external disturbance. The fixed-time stability of the system under the proposed composite control is proved by Lyapunov stability theory. Finally, the effectiveness of the method is verified by comparative simulation.

Each camera on digital devices is made of hundreds of thousands of sensors, with which it can separate and capture the light from spatial points in a fine-grain manner, enabling high-rate data transfer from the digital display to the camera, i.e. screen-camera communication. Compared with RF (Radio Frequency) technologies, visible light approaches are more convenient and secure.

There has been a great interest in recognizing gestures using wireless communication signals. We are motivated in detecting extremely fine, subtle finger gestures with WiFi signals. We envision this technology to find applications in finger-gesture control, disabled-friendly devices, physical therapy etc. The requirements of mm-level sensitivity and user-friendly feature using existing WiFi signals pose great challenges. Here, we present Mudra, a fine-grained finger gesture recognition system which leverages WiFi signals to enable a near-human-to-machine interaction with finger motion.

For a multicast group of n receivers, existing techniques either achieve high throughput at the cost of prohibitively large (e.g., O(n)) feedback overhead, or achieve low feedback overhead but without either optimal or near-optimal throughput guarantees. Simultaneously achieving good throughput guarantees and low feedback overhead has been an open problem and could be the key reason why wireless multicast has not been successfully deployed in practice. In this paper, we develop a novel anonymous-query based rate control, which approaches the optimal throughput with a constant feedback overhead independent of the number of receivers. In addition to our theoretical results, through implementation on a software-defined ratio platform, we show that the anonymous-query based algorithm achieves low-overhead and robustness in practice.

This paper describes the design and implementation of AirExpress, a system that enables in-band wireless cut-through transmission. Unlike wired cut-through, wireless cut-through can reduce latency and improve throughput performance of the network at the same time. In AirExpress, all the forwarders along the cut-through path forward the signal they received immediately without decoding. The hierarchical structure of AirExpress enables its interference cancellation ability to handle all kinds of interference among the radios. Novel MAC and routing algorithms based on cut-through transmission are also proposed to support the realization of AirExpress in multi-hop mesh networks.

Recent efforts in visible light communication over screen-camera links have exploited the display for data communications. Such practices, albeit convenient, have led to contention between space allocated for users and content reserved for devices, in addition to their aesthetic issues and distractive nature. In this paper, we propose InFrame--a system that enables dual-mode full-frame communication for both humans and devices simultaneously. InFrame leverages the temporal flick-fusion property of human vision system and the fast frame rate of modern display. It multiplexes data onto full-frame video contents through a novel complementary frame design and several other techniques. It thus ensures screen-camera data communication without affecting the primary video-viewing experience for human users. Our preliminary experiments have confirmed that InFrame can achieve about 12.8kbps data rate with imperceptible video artifacts when being played back at 120FPS.