Robot Architecture Research Articles

Neural Network-Based Adaptive Controller for Trajectory Tracking of Wheeled Mobile Robots

Trajectory tracking control is indispensable for a wheeled mobile robot to achieve successful navigation. The classical tracking control systems that are used in wheeled mobile robots do not compensate for the parameter uncertainties and external disturbances. For control strategy, this paper presents a novel hybrid approach, combining a neural network-based kinematic controller and a model reference adaptive control. The controller parameters are adaptively determined online using neural networks. The adaptively tuned kinematic controller ensures a fast convergence to the desired trajectory. The model reference adaptive controller retains the desired tracking performance when parameter and model uncertainties occur. The Lyapunov stability method is used to obtain the adaptive gains which guarantee the asymptotic stability of the error dynamics, where the error is the difference between the outputs of the reference model and the actual plant. The performance of the proposed controller is compared with that of the PID controller, kinematic controller, and adaptive dynamic controller using different performance analysis indices such as integral absolute error, integral squared error, and mean absolute error. Simulation studies demonstrate that the proposed controller achieves high tracking accuracy and fast convergence as compared to the PID, kinematic, and adaptive dynamic controllers considering parameter uncertainties and slip disturbances. The outcomes of the simulation studies also illustrate that the proposed controller achieves the best transient performance. Experiments using real-world tests based on a two-wheeled differential drive robot architecture have elucidated the feasibility of the developed controller regarding tracking accuracy, total control effort, and robustness against uncertainties.

Reorientation of Free-Falling Legged Robots

Abstract Based on the cat-righting reflex, this paper presents two reorientation maneuvers for legged robots that can produce roll and pitch reorientation during free fall. In order to better describe and plan these maneuvers, two separate, but equivalent, theoretical frameworks that describe the kinematic and dynamic behavior of free-floating articulated architectures are explored and developed. A nine-degree-of-freedom quadruped robot architecture is then presented and used to demonstrate the proposed maneuvers. Finally, kinematic and dynamic simulations of this architecture are performed. The results validate the presented theoretical framework and demonstrate that both roll and pitch reorientations are obtained through the application of the presented maneuvers.

Mimicking ion-balance-dependent synaptic plasticity in body fluid for adaptive environment-responsive artificial neuromuscular reflexes

Ions are the messengers by which nerve signals are transmitted, to endow a body with the ability to perceive the real world and react appropriately; the change of ion balance in body-fluid affects this ability in real-time. Here, we present the first artificial neuristor that uses transplantable ionic colloids and exhibits adaptive synaptic plasticity under different inner physiological states. Ion changes in the colloid replicate the loss of macro-elements (e.g. K+) and an overabundance of trace elements (e.g. Li+) in the body fluid; with disruption of the body-fluid balance, the excitatory synaptic responses were affected in varying degrees. The device was used for an environment-responsive reflex path by constructing a neuromuscular system, which shows a strong dependence on the balance states of the ionic medium. The proposed strategy could be applicable to next-generation neuromorphic architectures for bio-inspired electronics and humanoid robots.

The PoundCloud framework for ROS-based cloud robotics: Case studies on autonomous navigation and human–robot interaction

Despite the increasing popularity of the cloud robotics paradigm, the literature on the field still lacks comprehensive analysis on several aspects of the technology. Therefore, the adoption of common standards and frameworks is fundamental for developing the field and allowing practical works to be reproduced and compared. This work presents a ROS-based open framework for robot-cloud communication, easing the integration of robotics and remote cloud platforms, and discusses the implementation of the overall cloud robotics stack over open source software and commercial off-the-shelf devices. Additionally, we present two practical implementations in which most of the computation is carried out remotely and perform a series of experiments to demonstrate our technique. Our results indicate that task times can be reduced up to 15% when using remote cloud platforms even under 150 ms average communication latency over the public Internet while observing figures as low as 2% on throughput loss in sensor data transmission. In general, such results point to the feasibility of the presented approach in different classes of applications, even under non-ideal network and cloud settings.

Use of robots to encourage social engagement between older adults

We designed a robotic architecture system within a commercially available socially assistive robot to engage pairs of older adults in multimodal activities over 3 weeks for 6 sessions. The study took place in two assisted living facilities. Seven pairs (14 individuals) completed the experiment. Ages ranged from 70 to 90 years with a mean age of 83.0 (± 6.1). Most were women (79%). Three adults were screened as having normal cognition, 10 had mild cognitive impairment, and 1 adult self-reported a diagnosis of Alzheimer's disease. All sessions were video recorded and analyzed using Noldus Observer XT. Individuals demonstrated high levels of both human-human interaction and human-robot interaction, but the activity influenced the type of interaction. Engagement measures (visual, verbal, behavioral) also varied by type of activity. Future studies will focus on further development of activities that can engage older adults with varying levels of cognitive impairment and apathy.

A reference architecture for social robots

Social robotics poses tough challenges to software designers who are required to take care of difficult architectural drivers like acceptability, trust of robots as well as to guarantee that robots establish a personalized interaction with their users. Moreover, in this context recurrent software design issues such as ensuring interoperability, improving reusability and customizability of software components also arise. Designing and implementing social robotic software architectures is a time-intensive activity requiring multi-disciplinary expertise: this makes it difficult to rapidly develop, customize, and personalize robotic solutions. These challenges may be mitigated at design time by choosing certain architectural styles, implementing specific architectural patterns and using particular technologies. Leveraging on our experience in the MARIO project, in this paper we propose a series of principles that social robots may benefit from. These principles lay also the foundations for the design of a reference software architecture for social robots. The goal of this work is twofold: (i) Establishing a reference architecture whose components are unambiguously characterized by an ontology thus allowing to easily reuse them in order to implement and personalize social robots; (ii) Introducing a series of standardized software components for social robots architecture (mostly relying on ontologies and semantic technologies) to enhance interoperability, to improve explainability, and to favor rapid prototyping.

The Internet of Cooperative Agents Architecture (X-IoCA) for Robots, Hybrid Sensor Networks, and MEC Centers in Complex Environments: A Search and Rescue Case Study.

Cloud robotics and advanced communications can foster a step-change in cooperative robots and hybrid wireless sensor networks (H-WSN) for demanding environments (e.g., disaster response, mining, demolition, and nuclear sites) by enabling the timely sharing of data and computational resources between robot and human teams. However, the operational complexity of such multi-agent systems requires defining effective architectures, coping with implementation details, and testing in realistic deployments. This article proposes X-IoCA, an Internet of robotic things (IoRT) and communication architecture consisting of a hybrid and heterogeneous network of wireless transceivers (H2WTN), based on LoRa and BLE technologies, and a robot operating system (ROS) network. The IoRT is connected to a feedback information system (FIS) distributed among multi-access edge computing (MEC) centers. Furthermore, we present SAR-IoCA, an implementation of the architecture for search and rescue (SAR) integrated into a 5G network. The FIS for this application consists of an SAR-FIS (including a path planner for UGVs considering risks detected by a LoRa H-WSN) and an ROS-FIS (for real-time monitoring and processing of information published throughout the ROS network). Moreover, we discuss lessons learned from using SAR-IoCA in a realistic exercise where three UGVs, a UAV, and responders collaborated to rescue victims from a tunnel accessible through rough terrain.

Determination of the Inverse Kinematics Branches of Solution Based on Joint Coordinates for Universal Robots-Like Serial Robot Architecture

Abstract This paper introduces a classification of the inverse kinematics solutions (or robot postures) of six degrees-of-freedom serial robots with a geometry based on or similar to Universal Robots’ arms. The solution of the inverse kinematics problem is first presented briefly, and the equations required to classify the robot postures(branches) based on the joint coordinates are then introduced.

CREATION AND ANALYSIS OF THE STRUCTURE OF INTELLECTUAL DIAGNOSTIC SYSTEM OF INDUSTRIAL ROBOTS APPLIED IN EQUIPMENT MANUFACTURING

Based on comparative analysis of the current state of the issue, the main research tasks of the study were put in order to solve the current problem. The structure of the automated diagnostics system of typical industrial robots applied in flexible manufacturing systems of the appliance industry has been proposed. , The scheme of stable diagnostics of industrial robots applied in the flexible manufacturing system and also their mechatronics parts was proposed. To ensure the sustainability of the automated diagnostics of the industrial robot operating in the robotics complex, a scheme consisting of general diagnostic testing tools of the automated process control system, means of replacing faulty elements and diagnostic decision-making subsystem has been proposed. The automation scheme of the diagnostic system of technological equipment controlled by digital software, which is serviced by industrial robots in the flexible manufacturing system under study, has been proposed. The analysis of the proposed architecture of the industrial robot and its mechatronics diagnostic system was carried out. In one work turn, for the automated diagnosis of mechatronic parts of an industrial robot, the accuracy of its operations, hardness, power supply, oil content of mechanical parts, etc. requirements for verification of technical procedures have been identified. For the analysis of the architecture of the control and diagnostic system of the research object, the regulation of linear and angular displacements of the industrial robot at hierarchical levels (level 1), software testing of the current state of its execution mechanisms (level 2), automated workstation and control node connection is provided (level 3). For the automatic diagnostics of the industrial robot, the requirements for the sounds generated between the kinematic displacement points are in the accepted sound range, the vibrations in the kinematic displacement points are in the required range, and the power supply is in the required range. Automation of control and monitoring functions of the diagnostic system with the help of the server of the local industrial network of the industrial robot performing service functions in production is provided by SCADA. Keywords: instrumentation industry, flexible manufacturing system, diagnostic system, industrial robot, mechatronics part.

VisibleSim: A behavioral simulation framework for lattice modular robots

Simulation is one of the most important tools for robotics research, as it serves several crucial purposes such as prototyping, learning, avoiding dispensable hardware costs, or studying future systems that cannot be fabricated yet. Large scale self-reconfiguring modular robotic systems are an instance of such systems. Yet, current modular robotic simulators are overwhelmingly physics-based, which are good for real-world simulation but can be superfluous and sacrifice scalability when studying such systems through a behavioral lens. This paper introduces VisibleSim, an open-source behavioral simulator for lattice-based modular robots that uses discrete-event simulation. We describe the principles behind the simulator and introduce its features and usage from a user standpoint. VisibleSim has unique features like extensibility, versatility, and flexibility, it can also be used as a powerful visualization tool and has already a proven track record with several modular robotic architectures. We present a stress test composed of, ultimately, 32 million simulated robots, a new record in the field of modular robotic simulation.

A Study on Centralised and Decentralised Swarm Robotics Architecture for Part Delivery System

A Study on Centralised and Decentralised Swarm Robotics Architecture for Part Delivery System

A Study on Centralised and Decentralised Swarm Robotics Architecture for Part Delivery System

Academic Journal of Engineering Studies A Study on Centralised and Decentralised Swarm Robotics Architecture for Part Delivery System Angelos Dimakos1, Daniel Woodhall1 and Seemal Asif2* 1School of Aerospace, Transport and Manufacturing, Cranfield University, UK 2Centre for Structures, Assembly and Intelligent Automation, School of Aerospace, Transport and Manufacturing, Cranfield University, UK *Corresponding author: Seemal Asif, Centre for Structures, Assembly and Intelligent Automation, School of Aerospace, Transport and Manufacturing, Cranfield University, UK Submission: September 27, 2021 Published: October 11, 2021 DOI: 10.31031/AES.2021.02.000540 ISSN:2694-4421 Volume2 Issue3

Vision-based force distribution analysis for object catching

The problem of distribution of force, having the frictional contact between the passive object (manipulating) and active fingers (end-effector) of Delta robots, has been discussed. Computation of force components acting on the object’s points, given the wrench acting on the object and the contact points with respect to the body frame (estimated from the vision sensor) using combined parallel robot architecture, is performed. A pre-calibrated vision sensor was used for the pose estimation of the object. The proposed architecture design is intended to carry heavy payload objects for catching in the real-time scenario.

A Robot Architecture Using ContextSLAM to Find Products in Unknown Crowded Retail Environments

Grocery shoppers must negotiate cluttered, crowded, and complex store layouts containing a vast variety of products to make their intended purchases. This complexity may prevent even experienced shoppers from finding their grocery items, consuming a lot of their time and resulting in monetary loss for the store. To address these issues, we present a generic grocery robot architecture for the autonomous search and localization of products in crowded dynamic unknown grocery store environments using a unique context Simultaneous Localization and Mapping (contextSLAM) method. The contextSLAM method uniquely creates contextually rich maps through the online fusion of optical character recognition and occupancy grid information to locate products and aid in robot localization in an environment. The novelty of our robot architecture is in its ability to intelligently use geometric and contextual information within the context map to direct robot exploration in order to localize products in unknown environments in the presence of dynamic people. Extensive experiments were conducted with a mobile robot to validate the overall architecture and contextSLAM, including in a real grocery store. The results of the experiments showed that our architecture was capable of searching for and localizing all products in various grocery lists in different unknown environments.

A Multi-Agent Control Architecture for a Rescue Robot

Cognitive architectures investigate the components and interactions neccessary for construction of an intelligent system. Despite much progress and theory, implementations of architectures are rare. This research presents a novel cognitive architecture grounded in the design of a control system for an autonomous rescue robot. Experiments are conducted in high-fidelity 3D simulation of a rescue environment based on NISTs RoboCup Rescue.

Crossing Boundaries: Multi-Level Introspection in a Complex Robotic Architecture for Automatic Performance Improvements

Introspection mechanisms are employed in agent architectures toimprove agent performance. However, there is currently no approach tointrospection that makes automatic adjustments at multiple levels inthe implemented agent system. We introduce our novel multi-levelintrospection framework that can be used to automatically adjustarchitectural configurations based on the introspection results at theagent, infrastructure and component level. We demonstrate the utilityof such adjustments in a concrete implementation on a robot where thehigh-level goal of the robot is used to automatically configure thevision system in a way that minimizes resource consumption whileimproving overall task performance.

Socially Assistive Robots Serving Children with Special Needs (Autism, Cancer, Deafness/Hearing Loss)

One of the main challenges in social and cognitive research is relevant to our understanding of how to perceive and interact with others in the world around us. With the dramatic growth of emerging technologies in our societies, such as social robots, computer graphic generated avatars, and virtual reality devices, the complexity of this challenge is growing. As a result, interdisciplinary educators and researchers strive to determine the extent neurocognitive mechanisms, which support human interaction with artificial agents and tools, have evolved. Hence, a growing number of researchers working within the field of social robotics and engineering are engaged in collaboration with other scientists to utilize their expertise in social cognition, neuroscience, linguistics, and psychology with mutual interests that benefits naturally developing children as well as children with some form of disability and/or illness (i.e. Kids with: autism, cancer, deafness/hearing loss, down syndrome, diabetes, etc.). With the advancement of robotics technology, robots applications have been extended to more general-purpose practices in society such as: the use of robots in clinical and rehabilitation, nursing and elderly care, search and rescue operations, etc. However, for robotics technology to be successful in such environments it is necessary to gain new levels of strength, robustness, physical skills, and improved cognitive ability and intelligence. One faces many challenges on the path to design and construction of social-cognitive robots, the biggest is to build robots that comply with the needs and expectations of the human mind. How we communicate with machines with a higher quality physical and life-like appearance would differ with the way we interact with a computer, cell phone, or other smart devices. Therefore, as a follow up to the classical view of robotic systems, “socially interactive robots” with the capability of engaging social scenarios and interacting with humans have recently become a trendy and upto- date topic. In recent years, the impacts of employing social robots as teaching assistants on enhancing learners’ achievements notably in children with special needs were investigated by various researchers. In addition, these robots can be effectively employed in diverse healthcare applications. For instance, the positive effects of utilizing social robots in decreasing the distress level of children with cancer through establishing affective connection with patients was highlighted. Furthermore, they have been successfully utilized to improve the imitation skills of children with Autism Spectrum Disorder (ASD), which is known to be one of the core symptoms. In addition, social robots have been designed to play an assistive role in expanding the communication level of deaf and ordinary children in teaching them Sign Language. For instance, it has been noted that for social robots to achieve success in their mission, adaptive user interfaces lead to greater user acceptance and increased teaching efficiency compared to non-adaptive ones. Hence, one need to design and build a robotic architecture capable of simultaneously adjusting the robot’s teaching parameters according to both the user’s past and present performance, adapt the content of training, and then implement it on the social robot to teach sign language based on these parameters in a manner similar to a human teacher. On the other hand, empowering a robot to direct its attention to the most appropriate target at all times during multi-party interactions is another interesting and useful task to establish natural communication between the robot and users. Implementing a social gaze control system suitable for multiperson interactions with the social robot is another challenging topic, which may be done such that the system takes some important verbal and non-verbal social cues into account and at each moment enable the robot to decide socially at which human it should direct its gaze.

Brain emotional learning impedance control of uncertain nonlinear systems with time delay: Experiments on a hybrid elastic joint robot in telesurgery

Telesurgical robot control is a significant example of an uncertain nonlinear system, as it involves various complexities, including unknown master/slave dynamics, environmental uncertainties, joint elasticities, and communication time delays. This problem becomes even more complicated when desirable properties such as stability, transparency, rigidity, accuracy, and fine manipulability are considered. We consider an elastic joint telesurgical robot architecture that combines two parallel and serial manipulators to achieve the desired rigidity, accuracy, and fine manipulability. For this purpose, we propose using Brain Emotional Learning (BEL) to estimate the robot's uncertain nonlinear dynamics. In contrast to recent stability analyses of BEL-based systems, we employ Lyapunov theory to achieve the closed-loop system's general stability independent of robot dynamics and chattering. Furthermore, the proposed control architecture implements two reference impedance models for the master and slave robots' trajectory generation and makes a trade-off between transparency and stability by simultaneously considering optimal position synchronization and transparency conditions. In this regard, we extend these two conditions in absolute stability theory and Llewellyn's criterion to obtain the allowable bound of communication time delay. The proposed robot is designed and experimentally implemented at the Robotics Laboratories at FUM and SUT Universities. Along with confirming the theoretical results, simulations and laboratory experiments demonstrate that a reasonable trade-off between stability and transparency is made in four realistic case studies with and without communication time delays.

Client-Server Approach for Managing Visual Attention, Integrated in a Cognitive Architecture for a Social Robot

This paper proposes a novel system for managing visual attention in social robots. This system is based on a client/server approach that allows integration with a cognitive architecture controlling the robot. The core of this architecture is a distributed knowledge graph, in which the perceptual needs are expressed by the presence of arcs to stimuli that need to be perceived. The attention server sends motion commands to the actuators of the robot, while the attention clients send requests through the common knowledge representation. The common knowledge graph is shared by all levels of the architecture. This system has been implemented on ROS and tested on a social robot to verify the validity of the approach and was used to solve the tests proposed in RoboCup @ Home and SciROc robotic competitions. The tests have been used to quantitatively compare the proposal to traditional visual attention mechanisms.

ViMantic, a distributed robotic architecture for semantic mapping in indoor environments

Semantic maps augment traditional representations of robot workspaces, typically based on their geometry and/or topology, with meta-information about the properties, relations and functionalities of their composing elements. A piece of such information could be: fridges are appliances typically found in kitchens and employed to keep food in good condition. Thereby, semantic maps allow for the execution of high-level robotic tasks in an efficient way, e.g. “Hey robot, Store the leftover salad”. This paper presents ViMantic, a novel semantic mapping architecture for the building and maintenance of such maps, which brings together a number of features as demanded by modern mobile robotic systems, including: (i) a formal model, based on ontologies, which defines the semantics of the problem at hand and establishes mechanisms for its manipulation; (ii) techniques for processing sensory information and automatically populating maps with, for example, objects detected by cutting-edge CNNs; (iii) distributed execution capabilities through a client–server design, making the knowledge in the maps accessible and extendable to other robots/agents; (iv) a user interface that allows for the visualization and interaction with relevant parts of the maps through a virtual environment; (v) public availability, hence being ready to use in robotic platforms. The suitability of ViMantic has been assessed using Robot@Home, a vast repository of data collected by a robot in different houses. The experiments carried out consider different scenarios with one or multiple robots, from where we have extracted satisfactory results regarding automatic population, execution times, and required size in memory of the resultant semantic maps.