Intelligent Escape of Robotic Systems: A Survey of Methodologies, Applications, and Challenges

Intelligent escape is an interdisciplinary field that employs artificial intelligence (AI) techniques to enable robots with the capacity to intelligently react to potential dangers in dynamic, intricate, and unpredictable scenarios. As the emphasis on safety becomes increasingly paramount and advancements in robotic technologies continue to advance, a wide range of intelligent escape methodologies has been developed in recent years. This paper presents a comprehensive survey of state-of-the-art research work on intelligent escape of robotic systems. Four main methods of intelligent escape are reviewed, including planning-based methodologies, partitioning-based methodologies, learning-based methodologies, and bio-inspired methodologies. The strengths and limitations of existing methods are summarized. In addition, potential applications of intelligent escape are discussed in various domains, such as search and rescue, evacuation, military security, and healthcare. In an effort to develop new approaches to intelligent escape, this survey identifies current research challenges and provides insights into future research trends in intelligent escape.Comment: This paper is accepted by Journal of Intelligent and Robotic System

Effectiveness of Using MyFPGA Platform for Teaching Digital Logic

Accompanying electric circuits and computer programming, digital logic is deemed one of the most essential parts of any Electrical and Computer Engineering curriculum, so student success in the course is critical. Furthermore, research shows that the academic performance of students is heavily dependent upon student engagement, which is believed to increase with classroom strategies such as flipped-classrooms, cooperative learning, project-based learning, and virtual labs. The University of Texas Rio Grande Valley (UTRGV) is a Hispanic serving institution with distributive campuses, where many of the students work part-time. With consideration of the special needs of our students and the latest developments in engineering education, this study focuses on our recent experience of teaching digital logical using MyFPGA, online FPGA platform. We first introduce the MyFPGA platform in this paper. Developed by one of the authors of this paper, this web-based design features I/O interfacing circuits with an Intel FPGA hardware board as well as API web services with the Intel Quartus II design software. The platform provides 24/7 real-time hardware design experience at students’ fingertips, requiring only a web browser and internet access. It exposes the students to a complete engineering design cycle that includes problem specification, block diagram design, HDL source code design, simulation and hardware verification, trouble shooting and evaluation, and reporting. We consider different cases of the platform usage in two digital logic courses. To evaluate the effectiveness of the student learning experience, data is collected using outcome assessments, student feedback and self-evaluations, instructor observations, and comparative studies. Preliminary results confirmed the effectiveness of the online digital design platform. We have also identified a few pitfalls, such as instructors’ initial reluctance in adopting the platform and students’ first perception of the platform as a pure simulation tool. Based on the studies, recommendations are made to identify the best practices in the utilization of the platform to better serve Electrical and Computer Engineering majors and secondary school students interested in the general STEM fields

Approximate Solutions of Set-Valued Stochastic Differential Equations

Abstract In this paper, we consider the problem of approximate solutions of set-valued stochastic differential equations. We firstly prove an inequality of set-valued Itô integrals, which is related to classical Itô isometry, and an inequality of set-valued Lebesgue integrals. Both of the inequalities play an important role to discuss set-valued stochastic differential equations. Then we mainly state the Carathodory's approximate method and the Euler-Maruyama's approximate method for set-valued stochastic differential equations. We also investigate the errors between approximate solutions and accurate solutions

Acoustic tweezer with complex boundary-free trapping and transport channel controlled by shadow waveguides.

Acoustic tweezers use ultrasound for contact-free, bio-compatible, and precise manipulation of particles from millimeter to submicrometer scale. In microfluidics, acoustic tweezers typically use an array of sources to create standing wave patterns that can trap and move objects in ways constrained by the limited complexity of the acoustic wave field. Here, we demonstrate spatially complex particle trapping and manipulation inside a boundary-free chamber using a single pair of sources and an engineered structure outside the chamber that we call a shadow waveguide. The shadow waveguide creates a tightly confined, spatially complex acoustic field inside the chamber without requiring any interior structure that would interfere with net flow or transport. Altering the input signals to the two sources creates trapped particle motion along an arbitrary path defined by the shadow waveguide. Particle trapping, particle manipulation and transport, and Thouless pumping are experimentally demonstrated

Towards efficient and reconfigurable next-generation optical fronthaul networks for massive MIMO

This paper summaries our recent research on digital radio over fibre (DRoF) based optical fronthaul links and experimentally demonstrates a novel last-mile wireless coverage system incorporating data compression, time-division multiplexing (TDM) based packetization, and wavelength division multiplexing (WDM) based optical transmission. Compression reduces the fronthaul data rate required per service by a factor of 3 when compared with the common public radio interface (CPRI) standard, enabling efficient radio resource distribution over optical fibre infrastructure. The new packetization mechanism and WDM architecture enable fully reconfigurable resource allocation in a fronthaul network for 20MHz-bandwidth RF inputs with 64x64 MIMO carried over an aggregated compressed optical data rate of 32Gbps using 4 wavelengths. The experimental results show over 40dB RF dynamic range with < 8% error value magnitude (EVM) for the 64 quadrature amplitude modulation (64-QAM) input signals across all the WDM channels while the lowest EVM is less than 2%. Meanwhile, this field-programmable gate array (FPGA) based DRoF system allows flexible, software definable and easy-scalable dynamic antenna resource allocatio