Controller and actuator of three independent DC motors In closed loop

This article describes a solution for a high power controller and actuator of three DC motors in closed loop. This controller can be applied to omnidirectional platform solutions using three motorised Swedish wheels as used by several RobCup MSL robots and Minho omnidirectional Wheelchair. Some existing controllers in the market are reviewed pointing out their characteristics and comparing them with the proposed solution. Operational characteristics and developed algorithms of the proposed system are fully disclosed

Performing edge detection by difference of Gaussians using q-Gaussian kernels

In image processing, edge detection is a valuable tool to perform the extraction of features from an image. This detection reduces the amount of information to be processed, since the redundant information (considered less relevant) can be unconsidered. The technique of edge detection consists of determining the points of a digital image whose intensity changes sharply. This changes are due to the discontinuities of the orientation on a surface for example. A well known method of edge detection is the Difference of Gaussians (DoG). The method consists of subtracting two Gaussians, where a kernel has a standard deviation smaller than the previous one. The convolution between the subtraction of kernels and the input image results in the edge detection of this image. This paper introduces a method of extracting edges using DoG with kernels based on the q-Gaussian probability distribution, derived from the q-statistic proposed by Constantino Tsallis. To demonstrate the method's potential, we compare the introduced method with the traditional DoG using Gaussians kernels. The results showed that the proposed method can extract edges with more accurate details.Comment: 5 pages, 5 figures, IC-MSQUARE 201

Comparative genomic analysis of novel Acinetobacter symbionts : A combined systems biology and genomics approach

Acknowledgements This work was supported by University of Delhi, Department of Science and Technology- Promotion of University Research and Scientific Excellence (DST-PURSE). V.G., S.H. and U.S. gratefully acknowledge the Council for Scientific and Industrial Research (CSIR), University Grant Commission (UGC) and Department of Biotechnology (DBT) for providing research fellowship.Peer reviewedPublisher PD

An efficient adaptive data-link-layer architecture for LoRa networks

LoRa is one of the most popular low-power wireless network technologies for implementation of the Internet of Things, with the advantage of providing long-range communication, but lower data rates, when compared with technologies such as Zigbee or Bluetooth. LoRa is a single-channel physical layer technology on top of which LoRaWAN implements a more complex multi-channel network with enhanced functionalities, such as adaptive data rate. However, LoRaWAN relies on expensive hardware to support these functionalities. This paper proposes a LoRa data-link-layer architecture based on a multi-layer star network topology that adapts relevant LoRa parameters for each end node dynamically taking into account its link distance and quality in order to balance communication range and energy consumption. The developed solution is comprised of multiple components, including a LoRa parameter calculator to help the user to configure the network parameters, a contention-free MAC protocol to avoid collisions, and an adaptive spreading factor and transmission power mechanism. These components work together to ensure a more efficient use of the chosen ISM band and end node resources, but with low-cost implementation and operation requirements.This research was funded by FEDER through COMPETE2020—Programa Operacional Competitividade e Internacionalização (POCI) grant number POCI-01-0145-FEDER-028247 and by FCT—Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/202

Trends in the control of hexapod robots: a survey

The static stability of hexapods motivates their design for tasks in which stable locomotion is required, such as navigation across complex environments. This task is of high interest due to the possibility of replacing human beings in exploration, surveillance and rescue missions. For this application, the control system must adapt the actuation of the limbs according to their surroundings to ensure that the hexapod does not tumble during locomotion. The most traditional approach considers their limbs as robotic manipulators and relies on mechanical models to actuate them. However, the increasing interest in model-free models for the control of these systems has led to the design of novel solutions. Through a systematic literature review, this paper intends to overview the trends in this field of research and determine in which stage the design of autonomous and adaptable controllers for hexapods is.The first author received funding through a doctoral scholarship from the Portuguese Foundation for Science and Technology (FCT) (Grant No. SFRH/BD/145818/2019), with funds from the Portuguese Ministry of Science, Technology and Higher Education and the European Social Fund through the Programa Operacional Regional Norte. This work has been supported by the FCT national funds, under the national support to R&D units grant, through the reference project UIDB/04436/2020 and UIDP/04436/2020

Parallel, angular and perpendicular parking for self-driving cars using deep reinforcement learning

The progress in creating a fully autonomous selfdriving car has steadily increased in recent decades. Consequently, autonomous parking has been a well-researched field since every driving trip must end with a parking manoeuvre. In recent years, with the current successes in reinforcement learning, the concept of applying it to solve the autonomous parking problem has been more and more explored. A vehicle equipped with a complete autonomous parking system must perform three types of parking: perpendicular, angular and parallel parking. Autonomous parking systems control the steering angle and the vehicle speed by considering the surrounding space conditions to ensure collision-free motion within the available space. This paper presents an approach to the problem of autonomous parking using Reinforcement Learning, more precisely, Deep Deterministic Policy Gradient. This approach proved to be capable of parking in a variety of different environments for the three parking manoeuvres.This work has been supported by FCT-Fundacao para a Ciencia e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020. In addition, this work has also been funded through a doctoral scholarship from the Portuguese Foundation for Science and Technology (Fundacao para a Ciencia e a Tecnologia) [grant number SFRH/BD/06944/2020], with funds from the Portuguese Ministry of Science, Technology and Higher Education and the European Social Fund through the Programa Operacional do Capital Humano (POCH)

Hexapod posture control for navigation across complex environments

Hexapod locomotion in unstructured environments relies on an efficient posture adjustment with the terrain topology. This paper presents a strategy to adapt the hexapod torso orientation through ground plane estimation. With an Inertial Measurement Unit (IMU) and the robot kinematic model, the current supporting feet coordinates are calculated, and the relative inclination between the ground and the torso angular position can be obtained. This information is used to adjust the novel foothold positions, in order to ensure the hexapod posture remains stable. The torso height is also controlled to avoid collisions with the ground asperities and decrease its deviation during motion. The proposed method is evaluated in a complex terrain made of 0.1×0.1 m blocks with variable height, causing different slopes across the field. Through result analysis, a significant behavior improvement is observed, due to the reduction of the torso posture oscillation and the increase of its locomotion efficiency.The first author received funding through a doctoral scholarship from the Portuguese Foundation for Science and Technology (FCT) (Grant No. SFRH/BD/145818/2019), with funds from the Portuguese Ministry of Science, Technology and Higher Education and the European Social Fund through the Programa Operacional Regional Norte. This work has been supported by FCT within the R&D Units Project Scope: UIDB/00319/2020, UIDB/04436/2020 and UIDP/04436/2020

Study of the locomotion of a hexapod using CoppeliaSim and ROS

Generating adaptive locomotion has seen a growing interest for the design of hexapods due to improving the autonomy of these robots, allowing them to execute tasks in more demanding environments. Data from the robot’s surrounding must be acquired and processed to adjust the locomotion, and aid with the actuation of the six limbs. This paper aims at using force sensors placed on the feet of a hexapod to control the changes of the gait phase of each limb. These sensors also assist in the search of new footholds when no contact forces are established with the ground. The system is tested in a smooth irregular terrain with obstacles, steps, and ramps, using CoppeliaSim and ROS (Robot Operating System), to dynamically evaluate the behavior of the hexapod.(undefined

An integrated approach to assess the sublethal effects of colloidal gold nanorods in tadpoles of Xenopus laevis

Gold nanorods (AuNR) have been explored for many applications, including innovative nanomedicines, which also might contribute to its increase in the environment, namely due to inadequate disposable of wastes into aquatic environments. Early-life stages of amphibians are usually aquatic and sensitive to chemical contamination. Accordingly, this study aimed to determine the sublethal effects of CTAB functionalized AuNR on Xenopus laevis tadpoles. As such, tadpoles were exposed to serial concentrations of AuNR for 72 h. A reduction in the rate of feeding (EC50 = 4 μg.L-1), snout to vent growth (EC50 = 5 μg.L-1) and weight gain (EC50 = 6 μg.L-1), was observed for AuNR-exposed tadpoles. Also, tadpoles actively avoided concentrations ≥ 4 μg.L-1 of AuNR, after 12 h of exposure. At the biochemical level, AuNR caused impairments in antioxidant and nervous system related enzymes. Exposure to CTAB alone caused a high mortality. Results indicated that CTAB functionalized AuNR may induce several sublethal effects that may compromise the organism's fitness. Avoidance behavior (which corresponds to the disappearance of organisms, thus, similar to their death), observed at concentrations matching those inducing sublethal effects, suggest that it should be considered in the risk assessment for amphibians.publishe