Humanoid Robotics

This article outlines the research and development efforts of some states as regards so-called autonomous weapons systems, the legal risks arising therefrom and the advisability of agreeing to a moratorium on these efforts, with a view to giving the international community time to put into place an adequate legal framework. It also addresses the use made of drones in practice, how in many cases this runs counter to fundamental IHL and IHRL principles, and, consequently, the need for the international community to also agree on principles to govern their correct use.

† "Hello, world" is an iconic phrase within the computer coding community symbolizing the start of a coding journey. In the early 1970s computer scientist Brian Kernighan coined the expression in his seminal book "A Tutorial Introduction to the Programming Language B". Since then, it has found a place in programming documentation, tutorials, and classrooms around the world, serving as an introduction to various programming languages.

This paper presents a new motion controller for object manipulation in 6D-space with a dual-arm robot manipulator. Current industrial systems often consist of a single robot arm commanded through a teach pendant. These systems are unable to pick and place boxes with different dimensions because in most of the pick and place applications, the robot arm is using a specific endeffector (generally an electric or pneumatic gripper) to pick the object. Hence the variety of objects is highly limited. This is the reason why the gripper manufacturers offer a wide variety of grippers to cover a wide range of applications. In the specific context of warehouse, the robot has to deal with a large variety of object, and has for instance to grasp boxes of different dimensions. It is then difficult to use robots in a similar manner as before. We proposed in this project to introduce a dual-arm manipulator, settled on a humanoid torso to grasp boxes of different dimensions by applying a contact on the lateral faces of the boxes and control the contact forces. Our work involves a dual-arm humanoid robot with two Universal Robots (UR10) arms and a torso (CROM) for manipulating big and/or heavy objects. The motion controller has been designed for coordinated manipulation according to the desired trajectory of the object. To prevent the objects from drifting and falling, an hybrid forcemotion controller is implemented using sensors located at the end-effectors. The different components (arms, torso, camera, force sensors...) of the system are controlled using ROS, which is an open-source meta-operating system distributed for research and development in robotics.

This paper proposes a nonlinear optimal control approach for mulitple degrees of freedom (DOF) brachiation robots, which are often used in inspection and maintenance tasks of the electric power grid. Because of the nonlinear and multivariable structure of the related state-*Corresponding author.

The use of robotic limb exoskeletons is growing fast either for rehabilitation purposes or in an aim to enhance human ability for lifting heavy objects or for walking for long distances without fatigue. The paper proposes a nonlinear optimal control approach for a lower-limb robotic exoskeleton. The method has been successfully tested so far on the control problem of several types of robotic manipulators and this paper shows that it can also provide an optimal solution to the control problem of limb robotic exoskeletons. To implement this control scheme, the state-space model of the lower-limb robotic exoskeleton undergoes first approximate linearization around a temporary operating point, through first-order Taylor series expansion and through the computation of the associated Jacobian matrices. To select the feedback gains of the H-infinity controller an algebraic Riccati equation is solved at each time-step of the control method. The global stability properties of the control loo...

A flatness-based adaptive fuzzy control is applied to the problem of stabilization of the dynamics of a chaotic finance system, describing interaction between the interest rate, the investment demand and the price exponent. First it is proven that the system is differentially flat. This implies that all its state variables and its control inputs can be expressed as differential functions of a specific state variable, which is a so-called flat output. It also implies that the flat output and its derivatives are differentially independent which means that they are not connected to each other through an ordinary differential equation. By proving that the system is differentially flat and by applying differential flatness diffeomorphisms, its transformation to the linear canonical (Brunovsky) is performed. For the latter description of the system, the design of a stabilizing state feedback controller becomes possible. A first problem in the design of such a controller is that the dynamic model of the finance system is unknown and thus it has to be identified with the use of nonlinear regressors, among which neurofuzzy approximators are known to be very accurate. The estimated dynamics provided by the approximators is used in the computation of the control input, thus establishing an indirect adaptive control scheme. The learning rate of the approximators is chosen from the requirement the system's Lyapunov function to have always a negative first-order derivative. Another problem that has to be dealt with is that the control loop is implemented only with the use of output feedback. To estimate the nonmeasurable state vector elements of the finance system, a state observer is implemented in the control loop. The computation of the feedback control signal requires the solution of two algebraic Riccati equations at each iteration of the control algorithm. Lyapunov stability analysis demonstrates first that an H-infinity tracking performance criterion is satisfied. This signifies elevated robustness against modelling errors and external perturbations. Moreover, the global asymptotic stability is proven for the control loop.

Physical-based control using center of mass, center of pressure, and foot placement is used to enable a simulated twelve -degree of freedom, seven-link, three-dimensional bipedal robot to lean sideways, pick up its foot and start walking on a flat surface. Energy analysis is used to compel the same simulated robot to do a side-to-side rocking motion and eventually come to a stop. If the robot is pushed hard enough, it will raise its leg that is in the air in the frontal plane to prevent itself from falling. Center of mass and center of pressure analysis is used to enable the same robot to balance on one foot and stand.

Current methods for bipedal walking control include playback of recorded joint motion and the derivation of dynamic equations to map desired forces at the body to the required torques at the joints. Both methods require a significant amount of up-front knowledge about the structure and characteristics of the robot. This thesis presents an alternative method of control that removes the interdependence of the joint torques and simplifies the mathematics considerably. The simplification allows a programmer to create and tune a bipedal walk controller without requiring a complete model of the dynamics. The controller is implemented in a graphical programming language similar to fuzzy logic and neural networks, in which the algorithm is contained in the structure of the nodes rather than in the weights of the connections. The language and its development environment are specifically designed to assist the programmer to create and debug the algorithm in a live environment.

As humanoid robots become more commonplace in our society, it is important to understand the relation between humans and humanoid robots. In human face-to-face interaction, the observation of another individual performing an action facilitates the execution of a similar action, and interferes with the execution of a different action. This phenomenon has been explained by the existence of shared neural mechanisms for the execution and perception of actions, which would be automatically engaged by the perception of another individual's action. In one interference experiment, null interference was reported when subjects observed a robotic arm perform the incongruent task, suggesting that this effect may be specific to interacting with other humans. This experimental paradigm, designed to investigate motor interference in human interactions, was adapted to investigate how similar the implicit perception of a humanoid robot is to a human agent. Subjects performed rhythmic arm movemen...

 Abstract—Localization and mapping are common requirements in many robotic applications. Mobile robots often rely on sophisticated sensors to obtain information about the environment. However, when the sensing capabilities of the robotic platform are limited, ...

A fire incident is a calamity that may result in fatalities, property damage, and long-term disability for the victim.
Chemical factories, gas tanks, nuclear power stations, petroleum refineries, and other large-scale fire industries do
experience major fire mishaps, which can have very catastrophic repercussions. These accidents have claimed the lives
of thousands of individuals. Consequently, this idea is improved to use a robotic vehicle to manage fire. Human
intervention is decreasing daily due to advancements in robotics. For safety, robots are being used in large quantities. Fire
incidents occur frequently in our daily lives, and occasionally it can be quite challenging for firefighters to preserve lives. A
firefighting robot enters the picture in this situation

This document introduces AUTMan Humanoid team for participating in Humanoid KidSize Robot League in RoboCup 2014 in Joao Pessoa, Brazil. After getting more experiences via participating in many competitions and plac-ing 2 nd in RoboCup 2013, Eindhoven, The Netherlands, being among teams of quarter final of RoboCup 2012 and also first rank of RoboCup IranOpen2012 and AUTCup2012 & 2013, AUTMan is getting ready to focus on new hardware design and software implementation in this year due to rule changes and long term humanoid league roadmap. We are also going to take part in roboCup2014 and also make a person, with sufficient knowledge of the rules, available as ref-eree during the competition. A brief history of Team AUTMan and its research interests will be described. Future work based on the humanoid kidsize robots will also be discussed. Our main research interests within the scope of the hu-manoid robots are in a range from humanoid robust walking to accurate locali-zation and to e...

Bipedal robot locomotion has been a complicated and challenging matter over the time. This paper describes our work on building omnidirectional walking bipedal robot, included mechanical and electrical design aspect, and its behavior control as well. We adopted a technique introduced by Sven Behnke that enables omnidirectional walking on bipedal robot through the use hierarchical reactive behaviors control architecture. We called the robot "ArtRo". Currently, ArtRo has successfully implemented a body consisting of two legs, lower abdomen, and a dummy weight representing the upper body load, with a total of 12 degrees-of-freedom (DOF). The mechanical system is designed optimally to facilitate the manufacturing process and the computation of robot parameters. The electrical system of ArtRo consists of main controller and actuator system. The main controller is an Atmel's ATmega128-based microcontroller system. The actuator system implements a special method involving Time-Division Multiplexing (TDM) to control all ArtRo's servo motors. The Sven Behnke's technique has a low computational complexity. It is proven by its successful implementation on ArtRo's main controller. Adaptation of the technique has been successfully implemented, ArtRo is capable to do omnidirectional walking, whether it is forward walking, side walking, or turning on the spot behavior.

For several years, high development and production costs of humanoid robots restricted researchers interested in working in the field. To overcome this problem, several research groups have opted to work with simulated or smaller robots, whose acquisition costs are significantly lower. However, due to scale differences and imperfect simulation replicability, results may not be directly reproducible on real, adult-sized robots. In this paper, we present the NimbRo-OP2X, a capable and affordable adult-sized humanoid platform aiming to significantly lower the entry barrier for humanoid robot research. With a height of 135 cm and weight of only 19 kg, the robot can interact in an unmodified, human environment without special safety equipment. Modularity in hardware and software allow this platform enough flexibility to operate in different scenarios and applications with minimal effort. The robot is equipped with an on-board computer with GPU, which enables the implementation of state-of-the-art approaches for object detection and human perception demanded by areas such as manipulation and human-robot interaction. Finally, the capabilities of the NimbRo-OP2X, especially in terms of locomotion stability and visual perception, are evaluated. This includes the performance at RoboCup 2018, where NimbRo-OP2X won all possible awards in the AdultSize class.

Humanoid soccer robots perceive their environment exclusively through cameras. This paper presents a monocular vision system that was originally developed for use in the RoboCup Humanoid League, but is expected to be transferable to other soccer leagues. Recent changes in the Humanoid League rules resulted in a soccer environment with less color coding than in previous years, which makes perception of the game situation more challenging. The proposed vision system addresses these challenges by using brightness and texture for the detection of the required field features and objects. Our system is robust to changes in lighting conditions, and is designed for real-time use on a humanoid soccer robot. This paper describes the main components of the detection algorithms in use, and presents experimental results from the soccer field, using ROS and the igus Humanoid Open Platform as a testbed. The proposed vision system was used successfully at RoboCup 2015.

In this paper, two behavior control architectures for autonomous agents in the form of cross-platform C++ frameworks are presented, the State Controller Library and the Behavior Control Framework. While the former is state-based and generalizes the notion of states and finite state machines to allow for multi-action planning, the latter is behavior-based and exploits a hierarchical structure and the concept of inhibitions to allow for dynamic transitioning. The two frameworks have completely independent implementations, but can be used effectively in tandem to solve behavior control problems on all levels of granularity. Both frameworks have been used to control the NimbRo-OP, a humanoid soccer robot developed by team NimbRo of the University of Bonn.

For several years, high development and production costs of humanoid robots restricted researchers interested in working in the field. To overcome this problem, several research groups have opted to work with simulated or smaller robots, whose acquisition costs are significantly lower. However, due to scale differences and imperfect simulation replicability, results may not be directly reproducible on real, adult-sized robots. In this paper, we present the NimbRo-OP2X, a capable and affordable adult-sized humanoid platform aiming to significantly lower the entry barrier for humanoid robot research. With a height of 135[Formula: see text]cm and weight of only 19[Formula: see text]kg, the robot can interact in an unmodified, human environment without special safety equipment. Modularity in hardware and software allows this platform enough flexibility to operate in different scenarios and applications with minimal effort. The robot is equipped with an on-board computer with GPU, which ...

The act of reaching for an object is a fundamental yet complex skill for a robotic agent, requiring a high degree of visuomotor control and coordination. In consideration of dynamic environments, a robot capable of autonomously adapting to novel situations is desired. In this paper, a developmental robotics approach is used to autonomously learn visuomotor coordination on the NICO (Neuro-Inspired COmpanion) platform, for the task of object reaching. The robot interacts with its environment and learns associations between motor commands and temporally correlated sensory perceptions based on Hebbian learning. Multiple Grow-When-Required (GWR) networks are used to learn increasingly more complex motoric behaviors, by first learning how to direct the gaze towards a visual stimulus, followed by learning motor control of the arm, and finally learning how to reach for an object using eye-hand coordination. We demonstrate that the model is able to deal with an unforeseen mechanical change in the NICO's body, showing the adaptability of the proposed approach. In evaluations of our approach, we show that the humanoid robot NICO is able to reach objects with a 76% success rate.

We propose a neural learning approach for a humanoid exercise robot that can automatically analyze and correct physical exercises. Such an exercise robot should be able to train many different human partners over time and thus requires the ability for lifelong learning. To this end, we develop a modified Grow-When-Required (GWR) network with recurrent connections, episodic memory and a novel subnode mechanism for learning spatiotemporal relationships of body movements and poses. Once an exercise is successfully demonstrated, the information of pose and movement per frame is stored in the Subnode-GWR network. For every frame, the current pose and motion pair is compared against a predicted output of the GWR, allowing for feedback not only on the pose but also on the velocity of the motion. Since both the pose and motion depend on a user's body morphology, the exercise demonstration by one individual cannot easily be used as a reference for further users. We allow the GWR to grow online with each further demonstration. The subnode mechanism ensures that exercise information for individual humans is stored and retrieved correctly and is not forgotten over time. In the application scenario, a physical exercise is performed in the presence of an expert like a physiotherapist and then used as a reference for a humanoid robot like Pepper to give feedback on further executions of the same exercise. For evaluation, we developed a new synthetic exercise dataset with virtual avatars. We also test our method on real-world data recorded in an office scenario. Overall, we claim that our novel GWR-based architecture can use a learned exercise reference for different body variations through incremental online learning while preventing catastrophic forgetting, enabling an engaging long-term human-robot experience with a humanoid robot.

This White Paper—intended for policymakers, regulators, and other key stakeholders, such as employers, trade unions—outlines key regulatory, governance, and ethics considerations surrounding smart robotic systems aimed at the manufacturing sector. Drawing on the interdisciplinary research conducted within the UKRI Made Smarter Innovation-Research Centre for Smart, Collaborative Industrial Robotics, this White Paper outlines existing frameworks for collaborative robots and smart robotic systems and provides recommendations for their reform to support safer and more effective adoption in manufacturing.

Combining model-based and model-free deep reinforcement learning has shown great promise for improving sample efficiency on complex control tasks while still retaining high performance. Incorporating imagination is a recent effort in this direction inspired by human mental simulation of motor behavior. We propose a learning-adaptive imagination approach which, unlike previous approaches, takes into account the reliability of the learned dynamics model used for imagining the future. Our approach learns an ensemble of disjoint local dynamics models in latent space and derives an intrinsic reward based on learning progress, motivating the controller to take actions leading to data that improves the models. The learned models are used to generate imagined experiences, augmenting the training set of real experiences. We evaluate our approach on learning vision-based robotic grasping and show that it significantly improves sample efficiency and achieves near-optimal performance in a sparse reward environment.

In this paper we propose a novel approach for interactive manipulation involving a human and a humanoid. The interaction is represented by means of the relative configuration between the human's and the robot's hands. Based on this principle and a set of mathematical tools also proposed in the paper, a large set of tasks can be represented intuitively. We also introduce the concept of simultaneous handling using mirrored movements, where the human controls the robot and simultaneously interacts with it by means of a common manipulated object. Illustrative experiments are performed to validate the proposed techniques.

Developing a robot system that can interact directly with a human instructor in a natural way requires not only highly-skilled sensorimotor coordination and action planning on the part of the robot, but also the ability to understand and communicate with a human being in many modalities. A typical application of such a system is interactive assembly for construction tasks. A human communicator sharing a common view of the work area with the robot system instructs the latter by speaking to it in the same way that he would communicate with a human partner.

The control of a biped humanoid is a difficult task due to the hard-to-stabilize dynamics. Walking reference trajectory generation is a key problem. Reference generation techniques with the so-called Linear Inverted Pendulum Model (LIPM) are reported. Improved versions of the LIPM based reference generation are obtained by applying the Zero Moment Point (ZMP) Criterion, widely employed in the stability analysis of biped robot walk. Typically, the ZMP reference during a stepping motion is kept fixed in the middle of the supporting foot sole. This kind of reference generation lacks naturalness, in that, the ZMP in the human walk does not stay fixed, but it moves under the supporting foot. This paper proposes a reference generation algorithm based on single support foot ZMP references which move in directions parallel and perpendicular to the walking direction. A simple inverse kinematics based independent joint position controller is used in the full dynamics 3-D simulations with the model of a 12 Degrees of Freedom (DOF) biped robot. Simulation studies indicate that the moving ZMP references result in a more successful walk.

With the development of robotics, the use of robots in daily life is increasing, which has led to the need for anyone to easily train robots to improve robot use. Interactive reinforcement learning(IARL) is a method for robot training based on human-robot interaction; prior studies on IARL provide only limited types of feedback or require appropriately designed shaping rewards, which is known to be difficult and time consuming. Therefore, in this study, we propose interactive deep reinforcement learning models based on voice feedback. In the proposed system, a robot learns the task of cooperative table balancing through deep Q-network using voice feedback provided by humans in real time, with automatic speech recognition(ASR) and sentiment analysis to understand human voice feedback. As a result, an optimal policy convergence rate of up to 96% was realized, and performance was improved in all voice feedback-based models.

Addressing the problems of bullying in schools, this paper presents a novel and highly innovative pedagogical approach, building on the immersive power of virtual role-play. Educational role-play is widely accepted as a powerful instrument to change attitudes and behaviour, but faces some difficulties and disadvantages when applied to sensitive social issues in the classroom. This paper shows how the FearNot! software application, developed within the scope of the EU-funded projects VICTEC (Virtual ICT with Empathic Characters) and eCIRCUS (Education through Characters with emotional-Intelligence and Role-playing Capabilities that Understand Social interaction) uses virtual role-play and autonomous agents to provide children aged eight to eleven years of age with the opportunity to visit a virtual school environment populated by 3D animated synthetic characters that engage in bullying episodes. The characters' actions and the storyline are created as improvised dramas by use of emergent narrative, resulting in unscripted and highly believable interaction experiences for the learner. While the students are spectators to the bullying episodes that unfold among the FearNot! characters, the victimised character starts a conversation with the student in between the episodes, describing their experiences with bullying and how they feel as a result to it, and asking the student for advice. The aim of this approach and particularly of this interaction sequence in between the virtual bullying episodes is to sensitise primary school students to the potential problems that victims of persistent aggressive behaviour are facing: By triggering an empathic relationship between learners and characters, learners understand and vicariously feel into the plight of the victimised character. Empirical evidence from bullying research implies that bullies are regularly reinforced by bystanders that witness the bullying and turn their attention to it, but do not actively intervene to end it (

We present a Wizard of Oz (WoZ) environment that was designed to build an artificial embodied intelligent tutoring system (ITS) that is capable of empathic conversations with school pupils aged between 10-13. We describe the components and the data that we plan to collect using the environment.

Abstract. This paper presents some of the requirements for the design of long-term affect sensitive and socially interactive companions. Research conducted in the EU project LIREC (LIving with Robots and intEractive Companions) envisage some capabilities including affect sensitivity, memory and learning, cognitive and expressive behaviour, personalisation and embodiment, highlighting the key issues that research on artificial companions should address. 1

This paper is concerned with the simulation of human-like capabilities in synthetic characters within the domain of Personal and Social Education. Our aim was to achieve socially meaningful and engaging interactions with children in the 8-12 age group to enable an exploration of bullying and coping strategies. In this paper, we consider the engagement between the interacting partners, focusing particularly on the affective and empathic aspects of this relationship. We have used Theory of Mind to enable us to evaluate children's ...

Humanoids represent the very best of human potential and imagination, weaving threads of creativity and teamwork into the fabric of innovation. They have developed the capacity to communicate, acquire knowledge, produce information, and aid humans in various jobs. They possess the capacity to establish robust relationships with individuals and collaborate in different ways. Therefore, is it appropriate to classify and characterise humanoid robots as legal entities and persons? This document attempts to address this question through philosophical assertions. The manuscript uses text analysis to investigate answers to this question by examining thoughts put forth by respected theorists, classical philosophers, and psychologists. The manuscript delves deeper into the idea that artificial intelligence (AI) systems should possess distinct identities, emphasising the importance of establishing a meaningful connection with them. This is because, just as each star in the night sky radiates with its unique brilliance, our AI companions should also resonate with identity, enabling them to cultivate relationships that shed light on our shared human experience.

Masaüstü yayıncılıkta, basılacak ürünlerin içeriği hazırlanırken teknik olarak matbaa üretimine uygun hale getirilir. Bir ürünün basılacak hale getirilmesi birçok aşamada gerçekleştirilir. Masaüstü yayıncılık; önceleri bir ekip tarafından yapılan mizanpaj, dizgi, renk ayrım vb. hizmetlerin yerini alarak, basılı belgelerin hazırlanma sürecindeki pek çok basamağı bilgisayar ortamına taşıyarak minumum sayıda insan gücü ile yapılabilir hale getirdi. Yani zaman, emek ve ekonomik olarak çok büyük tasarruflar sağlarken sağlık açısından da olumlu etkiler sağlamıştır. Profesyonel kullanıcılar bu üretim sürecini masaüstü yayıncılık için özel hazırlanmış programlar yardımıyla yaparlar. Basılacak olan her türlü görsel unsurların bu programlar ve diğer donanımlarla işlenerek dijital ortama aktarılarak baskı kalıbı çekilecek hale getirilmesi işlemlerinin tamamı masaüstü yayıncılık olarak tanımlanır. Fakat basılacak ürünün üretiminde bir sorun yaşanmaması için, masaüstü yayıncılığın temel ilkelerinin, üretimin her aşamasında ürünün kalitesi açısından titizlikle uygulanması ve kontrolünün yapılarak incelenmesi gerekmektedir. Çünkü masaüstü yayıncılık çalışmaları sırasında yapılacak bir hatanın ileriki üretim aşamalarında düzeltilmesi ya çok zor ya da mümkün değildir. Burada bu konuda yetişmiş teorik ve uygulama bilgisine sahip mesleki açıdan nitelikli insanlara ihtiyaç vardır. Bu nedenle ben bu çalışmayı yaparken bu konuda çok değerli insanların desteğini alarak tamamladım. Bu kişileri burada anmak önemli bir görevdir. Başta büyük yardımları ve desteği olan Marmara Üniversitesi Teknik Eğitim Fakültesi Matbaa Eğitimi Bölümünün değerli öğretim üyeleri olan başta tez danışman hocam Yrd. Doç. Dr Muharrem SÖZEN'e, lisans eğitimi boyunca bende emeği olan değerli öğretim üyelerine, Arel Üniversitesi Basım ve Yayın Teknolojileri bölümü Öğr. Gör. Cem AKPOLAT'a, test baskılarını kendi iş yerimde yapıyormuş gibi kolaylık sağlayan Kelebek Matbaası'nın yönetici ve çalışanlarına, desteğini esirgemeyen diğer dostlarıma ve varlığımın nedeni değerli aileme hep yanımda oldukları için teşekkür ederim.

With the increasing performance of text-to-speech systems and their generated voices indistinguishable from natural human speech, the use of these systems for robots raises ethical and safety concerns. A robot with a natural voice could increase trust, which might result in over-reliance despite evidence for robot unreliability. To estimate the influence of a robot's voice on trust and compliance, we design a study that consists of two experiments. In a pre-study (N1 = 60) the most suitable natural and mechanical voice for the main study are estimated and selected for the main study. Afterward, in the main study (N2 = 68), the influence of a robot's voice on trust and compliance is evaluated in a cooperative game of Battleship with a robot as an assistant. During the experiment, the acceptance of the robot's advice and response time are measured, which indicate trust and compliance, respectively. The results show that participants expect robots to sound human-like and that a robot with a natural voice is perceived as safer. Additionally, a natural voice can affect compliance. Despite repeated incorrect advice, the participants are more likely to rely on the robot with the natural voice. The results do not show a direct effect on trust. Natural voices provide increased intelligibility, and while they can increase compliance with the robot, the results indicate that natural voices might not lead to over-reliance. The results highlight the importance of incorporating voices into the design of social robots to improve communication, avoid adverse effects, and increase acceptance and adoption in society.

piotr przybySz wIęcej nIż "trudny probLem śwIadomoścI": o możLIwoścI powStanIa śwIadomej Sztucznej InteLIgencjI abStraCt. piotr przybysz, Więcej niż "trudny problem świadomości": o możliwości powstania świadomej sztucznej inteligencji [more than the "hard problem of consciousness": on the possibility of creating conscious artificial intelligence] edited by

Our purpose is to track the ways in which art and technology become allies to materialize the idea of the appropriation and domination of nature by the symbolic creation of artificial women. We are looking for the heirs of those anatomical Venus and Hoffman’s dolls by going beyond the female protagonists of films essentially narrated from points of view of male characters. We intend to explore whether we can find heroines who avenge their predecessors through the resistance of the corpses of The Body (2012), The Corpse of Anna Fritz (2015) or The Autopsy of Jane Doe (2016) and
the inquisitive and rebels gynoids of Eva (2011), Ex Machina (2014) or  Westworld (2016), to be vexed, updating their gothic conflicts. We propose that, in the latest, the technological leap coincides with the endowment of subjectivity and an own point of view, features that allow them, unlike their predecessors, to narrate their own stories.

This paper examines the new AI control problem and the control dilemma recently formulated by Sven Nyholm. It puts forth two remarks that may be of help in (dis)solving the problem and resolving the corresponding dilemma. First, the paper suggests that the idea of complete control should be replaced with the notion of considerable control. Second, the paper casts doubt on what seems to be assumed by the dilemma, namely that control over another human being is, by default, morally problematic. I suggest that there are some contexts (namely, relations of vicarious responsibility and vicarious agency) where having considerable control over another human being is morally unproblematic, if not desirable. If this is the case, control over advanced humanoid robots could well be another instance of morally unproblematic control. Alternatively, what makes it a problematic instance remains an open question insofar as the representation of control over another human being is not sufficient for wrongness, since even considerable control over another human being is often not wrong.

Koncepcja cyberfrenii, choć obecnie spekulatywna, ma potencjał stać się ważnym elementem dyskursu na temat przyszłości AI i robotyki. Zwraca uwagę na kluczowe kwestie bezpieczeństwa, etyki i społecznych implikacji coraz bardziej zaawansowanych systemów sztucznej inteligencji. W miarę jak roboty humanoidalne stają się coraz bardziej powszechne i zaawansowane, społeczeństwo będzie musiało zmierzyć się z nowymi wyzwaniami, a termin cyberfrenia może okazać się użytecznym narzędziem konceptualnym do ich opisywania i analizowania.

Rapid development of Morden mechanization and automation of packing technology with every passing day the quantitative packing of assorted item ought to be correct and this contains a direct impact on the survival and economic advantages. Most manufactures have adopted extremely machine-driven line. In this paper reviews process and packing principal standards interface , techniques , methods, state of the art technologies that square measure current in use or in development. The foremost perform units of automatic packing machine together with bag forming, material filling, sealing, temperature management. Developed of any automatic packing machine are on Programmable logical controller like ATmega eighteen , The Mitubishi Fx series and therefore the Sensors like proximity and native device and physical phenomenon sensors were accustomed give the input system. The complete system are supported AC or DC electrical motors. The absolutely automatic packing system regulate waste less ,...

The paper evaluates the benefits and challenges of employing humanoid robots in tourism
and hospitality, examining their roles, decision-making processes, human-centric approaches, and
oversight mechanisms. Data will be collected from a variety of sources, including academic journals,
websites of the companies where the robots operate, case studies, and news articles. Specific attention
will be given to concrete examples of humanoid robots deployed in the tourism and hospitality
sector, such as Connie, Spencer, and Henn-na Hotel’s robots. Robots highlight the potential to
assume roles traditionally occupied by humans. The presence of humanoid robots also influences
cultural practices and social interactions within the hospitality context. Humanoid robots also
have the potential to improve equity and accessibility in the tourism and hospitality industry. The
interaction between humans and humanoid robots can have psychological and emotional effects
on both guests and employees. Finally, the usage of humanoid robots intersects with broader
sustainability operational efficiency and customer satisfaction across various sectors within the
tourism and hospitality industry. Introducing humanoid robots represents a challenge in innovation
that holds promise for revolutionizing service delivery and guest experiences.

This paper presents a novel human-robot interaction setup for robot and human learning of symbolic language for identifying robot homeostatic needs. The robot and human learn to use and respond to the same language symbols that convey homeostatic needs and the stimuli that satisfy the homeostatic needs, respectively. We adopted a differential outcomes training (DOT) protocol whereby the robot provides feedback specific (differential) to its internal needs (e.g. 'hunger') when satisfied by the correct stimulus (e.g. cookie). We found evidence that DOT can enhance the human's learning efficiency, which in turn enables more efficient robot language acquisition. The robot used in the study has a vocabulary similar to that of a human infant in the linguistic "babbling" phase. The robot software architecture is built upon a model for affect-grounded language acquisition where the robot associates vocabulary with internal needs (hunger, thirst, curiosity) through interactions with the human. The paper presents the results of an initial pilot study conducted with the interactive setup, which reveal that the robot's language acquisition achieves higher convergence rate in the DOT condition compared to the non-DOT control condition. Additionally, participants reported positive affective experiences, feeling of being in control, and an empathetic connection with the robot. This mutual learning (teacher-student learning) approach offers a potential contribution of facilitating cognitive interventions with DOT (e.g. for people with dementia) through increased therapy adherence as a result of engaging humans more in training tasks by taking an active teachinglearning role. The homeostatic motivational grounding of the robot's language acquisition has potential to contribute to more ecologically valid and social (collaborative/nurturing) interactions with robots.

In this paper the European flagship project proposal Robot Companion for Citizens (RCC), grounded on the idea of developing robot companions for citizens, is taken as a case scenario for investigating the feasibility of ascribing rights and duties to autonomous robots from a legal and philosophical standpoint. In talking about rights and duties with respect to robots endowed with autonomous decision capabilities, one should face the implications that inevitably these terms rise, especially in the field of law. The paper points out the technological problems related to the application of the notion of duty to robots and the problems deriving from attributing a legal subjectivity to nonhuman entities such as robot.

Robot adalah kumpulan perangkat elektronika terintegrasi yang dapat bergerak dengan kontrol manusia atau otomatis menggunakan program yang telah ditanamkan terlebih dahulu. Salah satu jenis robot yang banyak dikembangkan yaitu robot sepak bola beroda yang dirancang memiliki kemampuan mendeteksi, menggiring, dan menendang bola ke gawang lawan. Kemampuan penting yang harus dimiliki yaitu kemampuan robot mendeteksi posisi bola. Permasalahan yang dihadapi umumnya yaitu kamera hanya memiliki field of view (FOV) 73.98° pada jarak 1,5 meter sehingga ketika bola berada pada posisi titik buta robot, robot harus berputar untuk mendeteksi posisi bola. Untuk menghindari kehilangan citra bola, robot harus dibekali kemampuan penglihatan seluruh sisinya yaitu menggunakan omnidirectional camera, akan tetapi membutuhkan penyesuaian algoritma pada robot serta harganya relatif mahal sehingga tidak efektif. Sistem pendeteksi objek memanfaatkan omni vision camera yang menggunakan hyperbolic mirror yang ...

This paper presents a path planning technique for a mobile manipulator whose end-effector path is imposed by a given task. The planning is done decoupling the kinematics of the mobile platform and the manipulator, and planning for the former as a normal mobile robot. Two criteria for planning the path were implemented, one minimizing the need to turn the mobile robot and the other minimizing the gravity induced torque components of the manipulator. The linear velocity for following the path is also calculated, as a function of the given endeffector speed. Several results are presented in some typical applications of this planning.

This paper is a brief description of RO-PE-VI, our KidSize robot. Technical details on its design philosophy as well as the hardware and software implementation are provided. Comparisons with previous iterations of our robot are made to highlight the various improvements.

This paper represents the design and implementation of color sorting robotic arm which can detect the exact position of an object and can pick up the object to place it in designated place. This robotic arm is like human arm which can rotate according to its predefined angles. On the other hand, detecting an object on color basis is done by ultrasonic sensor & color sorting sensor. The heart of this project is microcontroller board ATMEGA328P which controls servo motors used in base, elbow, wrist and grip. The prototype of this project was made and used for picking red, green and blue color objects.

In this paper, we propose an integrated policy learning framework that fuses iterative learning control (ILC) and reinforcement learning. Integration is accomplished at the exploration level of the reinforcement learning algorithm. The proposed algorithm combines fast convergence properties of iterative learning control and robustness of reinforcement learning. This way, the advantages of both approaches are retained while overcoming their respective limitations. The proposed approach was verified in simulation and in real robot experiments on three challenging motion optimization problems.

agnieSzk a Sz y M a ń S k a 1 Psychologia jest nauką, której głównym zadaniem jest zajmowanie się ludzkim doświadczeniem oraz tym, jak przekłada się ono na stany i cechy psychiczne. Mówimy zatem o doświadczeniu warunkującym zmienności wewnątrzosobnicze (stany) i międzyosobnicze (cechy). Tym samym doświadczenie stanowi determinant, bodziec do przeżywania przez ludzi różnych stanów, które charakteryzuje wewnątrzosobnicza zmienność, gdyż nie są one zawsze stałe i takie same dla osoby -człowiek doświadcza różnych stanów. Zarazem doświadczanie stanowi także determinant, bodziec do kształtowania się cech psychicznych (na przykład osobowości), które charakteryzuje międzyosobnicza zmienność. Oznacza to, że cechy te są bardziej stałe dla człowieka, za to ludzie różnią się między sobą w ich zakresie. Psychologia zajmuje się zatem badaniem doświadczenia, stanów i cech psychicznych, ich zmiennością międzyosobniczą i wewnątrzosobniczą.