A Signal Distribution Network for Sequential Quantum-dot Cellular Automata Systems

The authors describe a signal distribution network for sequential systems constructed using the Quantum-dot Cellular Automata (QCA) computing paradigm. This network promises to enable the construction of arbitrarily complex QCA sequential systems in which all wire crossings are performed using nearest neighbor interactions, which will improve the thermal behavior of QCA systems as well as their resistance to stray charge and fabrication imperfections. The new sequential signal distribution network is demonstrated by the complete design and simulation of a two-bit counter, a three-bit counter, and a pattern detection circuit

Robotic Swarm Dispersion Using Gradient Descent Algorithm

Robotic swarms can be used in applications ranging from mapping and exploring to sensing, emergency relief, and many others. The increasing sizes of these swarms makes it necessary to use simple inexpensive individual robots to keep a reasonable total cost. This usually leads to robots with very limited capabilities. With these limitations, swarm designers must rely on software to enable the robots to efficiently perform essential tasks such as deployment, congregation, and navigation. This paper addresses the particular problem of robotic swarm dispersion. We present and test a method that uses the strength of the robots\u27 radio signals and the gradient descent algorithm to achieve an efficient swarm dispersion. The results show that, with swarms of 3, 5, 7, and 10 robots, the suggested method can consistently increase the average distance from a robot to the center of the swarm and consequently increase the swarm\u27s coverage area

Robotic Swarm Dispersion Using Gradient Descent Algorithm

Robotic swarms can be used in applications ranging from mapping and exploring to sensing, emergency relief, and many others. The increasing sizes of these swarms makes it necessary to use simple inexpensive individual robots to keep a reasonable total cost. This usually leads to robots with very limited capabilities. With these limitations, swarm designers must rely on software to enable the robots to efficiently perform essential tasks such as deployment, congregation, and navigation. This paper addresses the particular problem of robotic swarm dispersion. We present and test a method that uses the strength of the robots\u27 radio signals and the gradient descent algorithm to achieve an efficient swarm dispersion. The results show that, with swarms of 3, 5, 7, and 10 robots, the suggested method can consistently increase the average distance from a robot to the center of the swarm and consequently increase the swarm\u27s coverage area

Recursive Implementation of Gaussian Filters with Switching and Reset Hardware

This paper suggests the use of linear programming and curve fitting to approximate Gaussian filters with a combination of recursive linear-phase exponential filters. The switching and reset method is used to create a stable implementation of an otherwise unstable pole-zero cancelation in the exponential filters. The results show that an accurate approximation of a Gaussian filter, of any order, can be recursively implemented using only 18 constant coefficient multipliers and 26 adders

Creative Engineering for 2020

The United States National Academy of Engineering's seminal work, <i>The Engineer of 2020 – Visions of Engineering in the New Century</i>, was written to prepare industrial, governmental, and academic institutions for the future of engineering. The authors of the report state, "Emphasis on the creative process will allow more effective leadership in the development and application of next-generation technologies to problems of the future." In 2011, 2012, and 2013, engineering undergraduates from the Valparaiso University College of Engineering (Valparaiso, Indiana, USA) participated in a four-day off-site course focused on creativity, innovation, teamwork, and leading the creative process. The course was taught by members of the engineering faculty and included sessions and on-location tours (near Orlando, Florida) that were led by instructors from an external training organization. Pre- and post-course surveys identify a significant improvement in the students' understanding of the roles of creativity, innovation, and the roles of leadership, communication, and teamwork in the creative process

A modified SRF-PLL for phase and frequency measurement of single-phase systems

Abstract: In this work, a single phase phase-locked-loop (PLL) that uses a low-pass notch filter is proposed. The new PLL was derived from the synchronous reference frame PLL (SRF-PLL) in which the dq axis components were generated using the αβ reference signals. The single-phase grid voltage was used as the α component, whereas the αβ component was derived by delaying the grid voltage by 90° in phase. The dynamics of the proposed PLL were compared to those of the SRF-PLL. The frequency measurement using the new PLL showed better performance over the SRF-PLL and a second-order generalized integrator (SOGI) PLL. The proposed PLL displayed better performance under both variable frequency and distorted grid voltage conditions. Experimental results were used to validate the dynamics obtained from the simulation results. The proposed method adds very little complexity to the conventional SRF-PLL

Autonomous Identification of Local Agents in Multi-Agent Robotic Swarms

With the emergence of swarm intelligence and evolutionary algorithms, system designers are creating robotic swarms of continuously increasing sizes. As the size of a swarm increases, it is imperative to have a uniform program collectively downloaded on all the agents in it. These uniform programs impede the designer\u27s ability to designate distinct identities for various agents in the swarm. In this work we propose an algorithm that, when implemented in a robotic swarm, allows the locally interacting agents to autonomously designate unique identifications to each other at run time. The results show that when used on a small swarm of autonomous robots, running the algorithm led to a steady state where every agent in a local neighborhood was assigned a unique identification value

An RSS-based method for path navigation in miniature robotic swarms

Swarm robots are designed with very limited sensing and computing capabilities to reduce the robots’ cost without sacrificing their functionality. These limited capabilities make it necessary to develop algorithms and methodologies to enable the robots to perform tasks such as tracking, following, or even navigating a path. This paper addresses the particular problem of a robot navigating a path specified by stationary beacon robots. We suggest a method that combines the radio signal strength with trigonometry to achieve an effective path navigation methodology. The performance analysis shows that the robot travels on average (1.5N + 1) segments to complete a path lined up by N beacons as opposed to 2.5N segments when using the traditional tracking algorithm

Synthesis of Recursive Linear-Phase Filters for Fixed-Point Hardware Platforms

This study presents a methodology for recursive implementation of linear-phase finite impulse response (FIR) filters in fixed-point hardware platforms. The work uses a modified version of the switching and reset method to efficiently implement recursive linear-phase exponential filters. An error analysis is presented that defines the upper error bounds resulting from the switching and reset implementation of the exponential filters in fixed-point hardware. The exponential filters are then used as basis functions to synthesise other filters of interest. Gaussian filters are used as an example. The suggested recursive implementation delivers an accurate approximation of the Gaussian function. Unlike traditional techniques for implementing FIR filters, the hardware size of this recursive technique is O(1). In other words, increasing the order of a filter does not proportionally increase its hardware size. The results show that when implementing Gaussian filters on FPGAs, doubling the size of the filter, only increased the hardware size by an average of 6.12%

Synthesis of Recursive Linear-Phase Filters for Fixed-Point Hardware Platforms

This study presents a methodology for recursive implementation of linear-phase finite impulse response (FIR) filters in fixed-point hardware platforms. The work uses a modified version of the switching and reset method to efficiently implement recursive linear-phase exponential filters. An error analysis is presented that defines the upper error bounds resulting from the switching and reset implementation of the exponential filters in fixed-point hardware. The exponential filters are then used as basis functions to synthesise other filters of interest. Gaussian filters are used as an example. The suggested recursive implementation delivers an accurate approximation of the Gaussian function. Unlike traditional techniques for implementing FIR filters, the hardware size of this recursive technique is O(1). In other words, increasing the order of a filter does not proportionally increase its hardware size. The results show that when implementing Gaussian filters on FPGAs, doubling the size of the filter, only increased the hardware size by an average of 6.12%