Advanced trajectory generator for two carts with RGB-D sensor on circular rail

This paper presents a motorised circular rail that generates the motion of two carts with an RGB-D sensor each. The objective of both carts' trajectory generation is to track a person's physical rehabilitation exercises from two points of view and his/her emotional state from one of these viewpoints. The person is moving freely his/her position and posture within the circle drawn by the motorised rail. More specifically, this paper describes the calculation of trajectories for safe motion of the two carts on the motorised circular rail in detail. Lastly, a study case is offered to show the performance of the described control algorithms for trajectory generation.- This work was partially supported by Ministerio de Ciencia, Innovacion y Universidades, Agencia Estatal de Investigacion (AEI) / European Regional Development Fund (FEDER, UE) under DPI2016-80894-R grant

Strategies of Balancing: Regulation of Posture as a Complex Phenomenon

The complexity of the interface between the muscular system and the nervous system is still elusive. We investigated how the neuromuscular system functions and how it is influenced by various perturbations. Postural stability was selected as the model system, because this system provides complex output, which could indicate underlying mechanisms and feedback loops of the neuromuscular system. We hypothesized that aging, physical pain, and mental and physical perturbations affect balancing strategy, and based on these observations, we constructed a model that simulates many aspects of the neuromuscular system. Our results show that aging changes the control strategy of balancing from more chaotic to more repetitive. The chaotic elements ensure quick reactions and strong capacity to compensate for the perturbations; this adeptly reactive state changes into a less reactive, slower, probably less mechanically costly balancing strategy. Mental tasks during balancing also decreased the chaotic elements in balancing strategy, especially if the subject experienced chronic pain. Additional motoric tasks, such as tying knots while balancing, were correlated with age but unaffected by chronic pain. Our model competently predicted the experimental findings, and we proceeded to use the model with an external data set from Physionet to predict the balancing strategy of Parkinson’s patients. Our neurological model, comprised of RLC circuits, provides a mechanistic explanation for the neuromuscular system adaptations

Multi-robot system control using artificial immune system

For the successful deployment of task-achieving multi-robot systems (MRS), the interactions must be coordinated among the robots within the MRS and between the robots and the task environment. There have been a number of impressive experimentally demonstrated coordinated MRS. However it is still of a premature stage for real world applications. This dissertation presents an MRS control scheme using Artificial Immune Systems (AIS). This methodology is firmly grounded in the biological sciences and provides robust performance for the intertwined entities involved in any task-achieving MRS. Based on its formal foundation, it provides a platform to characterize interesting relationships and dependencies among MRS task requirements, individual robot control, capabilities, and the resulting task performance. The work presented in this dissertation is a first of its kind wherein the principles of AIS have been used to model and organize the group behavior of the MRS. This has been presented in the form of a novel algorithm. In addition to the above, generic environments for computer simulation and real experiment have been realized to demonstrate the working of an MRS. These could potentially be used as a test bed to implement other algorithms onto the MRS. The experiment in this research is a bomb disposal task which involves a team of three heterogeneous robots with different sensors and actuators. And the algorithm has been tested practically through computer simulations.Mechanical Engineerin

Optimizing Associative Information Transfer within Content-addressable Memory

Original article can be found at: http://www.oldcitypublishing.com/IJUC/IJUC.htmlPeer reviewe

Abstractions, Analysis Techniques, and Synthesis of Scalable Control Strategies for Robot Swarms

Tasks that require parallelism, redundancy, and adaptation to dynamic, possibly hazardous environments can potentially be performed very efficiently and robustly by a swarm robotic system. Such a system would consist of hundreds or thousands of anonymous, resource-constrained robots that operate autonomously, with little to no direct human supervision. The massive parallelism of a swarm would allow it to perform effectively in the event of robot failures, and the simplicity of individual robots facilitates a low unit cost. Key challenges in the development of swarm robotic systems include the accurate prediction of swarm behavior and the design of robot controllers that can be proven to produce a desired macroscopic outcome. The controllers should be scalable, meaning that they ensure system operation regardless of the swarm size. This thesis presents a comprehensive approach to modeling a swarm robotic system, analyzing its performance, and synthesizing scalable control policies that cause the populations of different swarm elements to evolve in a specified way that obeys time and efficiency constraints. The control policies are decentralized, computed a priori, implementable on robots with limited sensing and communication capabilities, and have theoretical guarantees on performance. To facilitate this framework of abstraction and top-down controller synthesis, the swarm is designed to emulate a system of chemically reacting molecules. The majority of this work considers well-mixed systems when there are interaction-dependent task transitions, with some modeling and analysis extensions to spatially inhomogeneous systems. The methodology is applied to the design of a swarm task allocation approach that does not rely on inter-robot communication, a reconfigurable manufacturing system, and a cooperative transport strategy for groups of robots. The third application incorporates observations from a novel experimental study of the mechanics of cooperative retrieval in Aphaenogaster cockerelli ants. The correctness of the abstractions and the correspondence of the evolution of the controlled system to the target behavior are validated with computer simulations. The investigated applications form the building blocks for a versatile swarm system with integrated capabilities that have performance guarantees

Control and Coordination in a Networked Robotic Platform

Control and Coordination of the robots has been widely researched area among the swarm robotics. Usually these swarms are involved in accomplishing tasks assigned to them either one after another or concurrently. Most of the times, the tasks assigned may not need the entire population of the swarm but a subset of them. In this project, emphasis has been given to determination of such subsets of robots termed as ”flock” whose size actually depends on the complexity of the task. Once the flock is determined from the swarm, leader and follower robots are determined which accomplish the task in a controlled and cooperative fashion. Although the entire control system,which is determined for collision free and coordinated environment, is stable, the results show that both wireless (bluetooth) and internet (UDP) communication system can introduce some lag which can lead robot trajectories to an unexpected set. The reason for this is each robot and a corresponding computer is considered as a complete robot and communication between the robot and the computer and between the computers was inevitable. These problems could easily be solved by integrating a computer on the robot or just add a wifi transmitter/receiver on the robot. On going down the lane, by introducing smarter robots with different kinds of sensors this project could be extended on a large scale for varied heterogenous and homogenous applications

A Grey Wolf Optimization-Based Clustering Approach for Energy Efficiency in Wireless Sensor Networks

In the realm of Wireless Sensor Networks, the longevity of a sensor node's battery is pivotal, especially since these nodes are often deployed in locations where battery replacement is not feasible. Heterogeneous networks introduce additional challenges due to varying buffer capacities among nodes, necessitating timely data transmission to prevent loss from buffer overflows. Despite numerous attempts to address these issues, previous solutions have been deficient in significant respects. Our innovative strategy employs Grey Wolf Optimization for Cluster Head selection within heterogeneous networks, aiming to concurrently optimise energy efficiency and buffer capacity. We conducted comprehensive simulations using Network Simulator 2, with results analysed in MATLAB, focusing on metrics such as energy depletion rates, remaining energy, node-to-node distance, node count, packet delivery, and average energy in the cluster head selection process. Our approach was benchmarked against leading protocols like LEACH and PEGASIS, considering five key performance indicators: energy usage, network lifespan, the survival rate of nodes over time, data throughput, and remaining network energy. The simulations demonstrate that our Grey Wolf Optimisation method outperforms conventional protocols, showing a 9% reduction in energy usage, a 12% increase in node longevity, a 9.8% improvement in data packet delivery, and a 12.2% boost in data throughput

A Framework for Optical Inspection Applications in Life-Science Automation

This thesis presents possible applications for Computer Vision based systems in the field of Laboratory Automation and applicable camera-based, multi-camera-based or flatbed scanner based imaging devices. A concept of a software framework for CV applications is developed with respect to hardware compatibility, data processing and user interfaces. An application is implemented using the framework. It aims at the detection of low-volume liquids in microtiter plates, a labware standard. Using this algorithm, it is possible to cover a wide range of labware on different imaging hardware