Anthropomorphic Robotic System Research Articles

Anthropomorphic Tendon-Based Hands Controlled by Agonist-Antagonist Corticospinal Neural Network.

This article presents a study on the neurobiological control of voluntary movements for anthropomorphic robotic systems. A corticospinal neural network model has been developed to control joint trajectories in multi-fingered robotic hands. The proposed neural network simulates cortical and spinal areas, as well as the connectivity between them, during the execution of voluntary movements similar to those performed by humans or monkeys. Furthermore, this neural connection allows for the interpretation of functional roles in the motor areas of the brain. The proposed neural control system is tested on the fingers of a robotic hand, which is driven by agonist-antagonist tendons and actuators designed to accurately emulate complex muscular functionality. The experimental results show that the corticospinal controller produces key properties of biological movement control, such as bell-shaped asymmetric velocity profiles and the ability to compensate for disturbances. Movements are dynamically compensated for through sensory feedback. Based on the experimental results, it is concluded that the proposed biologically inspired adaptive neural control system is robust, reliable, and adaptable to robotic platforms with diverse biomechanics and degrees of freedom. The corticospinal network successfully integrates biological concepts with engineering control theory for the generation of functional movement. This research significantly contributes to improving our understanding of neuromotor control in both animals and humans, thus paving the way towards a new frontier in the field of neurobiological control of anthropomorphic robotic systems.

Ion trap and release dynamics enables nonintrusive tactile augmentation in monolithic sensory neuron.

An iontronic-based artificial tactile nerve is a promising technology for emulating the tactile recognition and learning of human skin with low power consumption. However, its weak tactile memory and complex integration structure remain challenging. We present an ion trap and release dynamics (iTRD)-driven, neuro-inspired monolithic artificial tactile neuron (NeuroMAT) that can achieve tactile perception and memory consolidation in a single device. Through the tactile-driven release of ions initially trapped within iTRD-iongel, NeuroMAT only generates nonintrusive synaptic memory signals when mechanical stress is applied under voltage stimulation. The induced tactile memory is augmented by auxiliary voltage pulses independent of tactile sensing signals. We integrate NeuroMAT with an anthropomorphic robotic hand system to imitate memory-based human motion; the robust tactile memory of NeuroMAT enables the hand to consistently perform reliable gripping motion.

Visions of Artificial Intelligence and Robots in Science Fiction: a computational analysis.

Driven by the rapid development of artificial intelligence (AI) and anthropomorphic robotic systems, the various possibilities and risks of such technologies have become a topic of urgent discussion. Although science fiction (SF) works are often cited as references for visions of future developments, this framework of discourse may not be appropriate for serious discussions owing to technical inaccuracies resulting from its reliance on entertainment media. However, these science fiction works could help researchers understand how people might react to new AI and robotic systems. Hence, classifying depictions of artificial intelligence in science fiction may be expected to help researchers to communicate more clearly by identifying science fiction elements to which their works may be similar or dissimilar. In this study, we analyzed depictions of artificial intelligence in SF together with expert critics and writers. First, 115 AI systems described in SF were selected based on three criteria, including diversity of intelligence, social aspects, and extension of human intelligence. Nine elements representing their characteristics were analyzed using clustering and principal component analysis. The results suggest the prevalence of four distinctive categories, including human-like characters, intelligent machines, helpers such as vehicles and equipment, and infrastructure, which may be mapped to a two-dimensional space with axes representing intelligence and humanity. This research contributes to the public relations of AI and robotic technologies by analyzing shared imaginative visions of AI in society based on SF works.

Human-Inspired Haptic-Enabled Learning From Prehensile Move Demonstrations

Research on robotic manipulation of fragile, compliant objects, such as food items, is gaining traction due to its game-changing potential within the food production and retailing sectors, currently characterized by manually-intensive and highly repetitive tasks. Food products exhibit high levels of frailness, biological variation, and complex 3D shapes and textures. For these reasons, introducing greater levels of robotic automation in the food and agricultural sectors remains an important challenge. This paper addresses this challenge by developing a human-centred, haptic-based, Learning from Demonstration (LfD) policy that enables pre-trained autonomous grasping of food items using an anthropomorphic robotic system. The policy combines data from teleoperation and direct human manipulation of objects, embodying human intent and interaction areas of significance. We evaluated the proposed solution against a recent state-of-the-art LfD policy as well as against two standard impedance controller techniques. Results show that the proposed policy performs significantly better than the other considered techniques, leading to high grasping success rates while guaranteeing the integrity of the food at hand.

Some Results of Experimentation with the Anthropomorphic Robotic System in Remote Control Master-Slave Mode.

At present, the requirements for the characteristics of the “cosmonaut-anthropomorphic robotic system-environment” ergatic system, the procedure for evaluating the performance of a cosmonaut-operator when using anthropomorphic robots, proposals for the functionality of this ergatic system and the ways of its application in order to increase the operational quality of existing and future manned space complexes can be determined and substantiated only as a result of carrying out experimental studies using an anthropomorphic robotic system.

Self-Powered Wearable Pressure Sensors with Enhanced Piezoelectric Properties of Aligned P(VDF-TrFE)/MWCNT Composites for Monitoring Human Physiological and Muscle Motion Signs.

Self-powered operation, flexibility, excellent mechanical properties, and ultra-high sensitivity are highly desired properties for pressure sensors in human health monitoring and anthropomorphic robotic systems. Piezoelectric pressure sensors, with enhanced electromechanical performance to effectively distinguish multiple mechanical stimuli (including pressing, stretching, bending, and twisting), have attracted interest to precisely acquire the weak signals of the human body. In this work, we prepared a poly(vinylidene fluoride-trifluoroethylene)/ multi-walled carbon nanotube (P(VDF-TrFE)/MWCNT) composite by an electrospinning process and stretched it to achieve alignment of the polymer chains. The composite membrane demonstrated excellent piezoelectricy, favorable mechanical strength, and high sensitivity. The piezoelectric coefficient d33 value was approximately 50 pm/V, the Young’s modulus was ~0.986 GPa, and the sensitivity was ~540 mV/N. The resulting composite membrane was employed as a piezoelectric pressure sensor to monitor small physiological signals including pulse, breath, and small motions of muscle and joints such as swallowing, chewing, and finger and wrist movements. Moderate doping with carbon nanotubes had a positive impact on the formation of the β phase of the piezoelectric device, and the piezoelectric pressure sensor has the potential for application in health care systems and smart wearable devices.

Motion Planning by Demonstration With Human-Likeness Evaluation for Dual-Arm Robots

This paper presents a planning procedure that allows an anthropomorphic dual-arm robotic system to perform a manipulation task in a natural human-like way by using demonstrated human movements. The key idea of the proposal is to convert the demonstrated trajectories into attractive potential fields defined over the configuration space and then use an RRT*-based planning algorithm that minimizes a path-cost function designed to bias the tree growth toward the human-demonstrated configurations. This paper presents a description of the proposed approach as well as results from a conceptual and a real application example, the latter using a real anthropomorphic dual-arm robotic system. A path-quality measure, based on first-order synergies (correlations between joint velocities) obtained from real human movements, is also proposed and used for evaluation and comparison purposes. The obtained results show that the paths obtained with the proposed procedure are more human-like.

First-Order Synergies for Motion Planning of Anthropomorphic Dual-Arm Robots

This paper addresses the problem of designing a planning algorithm for anthropomorphic dual-arm robotic systems to find paths that mimics the movements of real human beings by using first-order synergies (correlations between joint velocities). The key idea of the proposal is to convert captured human movements into a vector field of velocities, defined in the configuration space of the robot, and use it to guide the search of a solution path. The motion planning is solved using the proposed algorithm, called FOS-BKPIECE, that is a bidirectional version of the KPIECE planner working with an improved version of the extension procedure of the VF-RRT planner. The obtained robot movements follow the directions of the defined vector field and hence allow the robot to solve the task in a human-like fashion. The paper presents a description of the proposed approach as well as results from conceptual and application examples, the latter using a real anthropomorphic dual-arm robotic system. A thorough comparison with other previous planning algorithms shows that the proposed approach obtains better results.

The Inverse Kinematics of the Plane System 2-3 in a Mechatronic MP2R System, by a Trigonometric Method

Robots have penetrated today in almost all industrial fields, being much more precise than humans in the execution of operations, but also faster, more dynamic, more stable and more resilient, working 24 h of the 24 h possible, in any season, breaks, holidays, vacations and especially without getting sick. The most important fact is that they can also perform special operations that man can’t do. So, for example, they can work in toxic, contaminated, mined, dangerous, or airless environments (in the cosmos, under water or underground), they can also position the parts very precisely so they can be used for fine, special processing at high precision operations, excellent mechanical processing, exceptional medical operations and even in all medical operations today, helping the doctor manage the patient's surgery with amazing precision, especially when it comes to open heart, brain, kidneys, liver, etc. Robots should not be fed and yet they can have an extremely long life. They can help us conquer both the underwater spaces and the cosmic spaces. Robots have stunning work precision and a faster execution speed than a man. In addition, their very precise positioning makes robot operations a great advantage, which can no longer be neglected. In repetitive and tiring work they are irreplaceable. The most commonly used anthropomorphic robotic mechatronic systems, which are currently being used, have been studied by eliminating the heavy, matrix 3D spatial system, the study being simplified in a plan by considering the main work plan of the system and the plan, the rotation required to restore the spatial parameters of the anthropomorphic 3D system. In other words, we can greatly ease the work of the anthropomorphic robot engineer by moving from 3D systems to a 2D system. In this study we will study the inverse cinematics of the plan system, 2D, as the most important one. In general, end effector positions are known (required) and the positions of the 2D module elements and the necessary rotations of the actuators for their creation must be determined. In the kinematics we know the kinematic parameters xM and yM, which represent the scaled coordinates of the point M (endeffector M) and must be determined by analytical calculations the parameters φ20 and φ30.

Anthropomorphic Solid Structures n-R Kinematics

This paper presents and treats (in an original way) the specific elements of the structures of robotic solid mobile anthropomorphic type. Are placed on the wallpaper, the geometry and kinematics of the anthropomorphic robotic solid systems, in an original vision of the authors. One presents the inverse kinematics of anthropomorphic systems, with mechanical elements and points: Geometry, cinematic, positions, displacements, velocities and accelerations. They will be presented further two methods (as the most representatives): First one the method trigonometric and second one the geometric method.

Improving energy efficiency of a robotic system based on multiple analytical solutions for inverse kinematics

The paper presents the results of a study devoted to the problem of improving the energy efficiency of mechanical motion of anthropomorphic robotic systems. Achieving higher energy efficiency is largely due to the implementation of improvements directly in the algorithms that ensure the movement of a robotic system. For this purpose, several existing analytical methods for solving the inverse kinematics problem for robotic walking platforms were analyzed. According to the survey, key areas where modification can improve the energy efficiency of mechanical motion in various RS are identified. The paper discusses the algorithm developed to optimize the solutions of the inverse kinematics problem in terms of energy consumption.

Модернизация программно-аппаратного обеспечения модельных сервоприводов для использования в антропоморфных робототехнических комплексах

Модернизация программно-аппаратного обеспечения модельных сервоприводов для использования в антропоморфных робототехнических комплексах

An anthropomorphic design for a minimally invasive surgical system based on a survey of surgical technologies, techniques and training

Over the past century, abdominal surgery has seen a rapid transition from open procedures to less invasive methods, such as robot-assisted minimally invasive surgery (MIS). This study aimed to investigate and discuss the needs of MIS in terms of instrumentation and to inform the design of a novel instrument. A survey was conducted among surgeons regarding their opinions on surgical training, surgical systems, how satisfied they were with them and how easy they were to use. A concept for MIS robotic instrumentation was then developed and a series of focus groups with surgeons were run to discuss it. The initial prototype of the robotic instruments, herein demonstrated, comprises modular rigid links with soft joints actuated by shape memory alloy helix actuators; these instruments are controlled using a sensory hand exoskeleton. The results of the survey, as well as those of the focus groups, are presented here. A first prototype of the system was built and initial laboratory tests have been conducted in order to evaluate this approach. The analysed data from both the survey and the focus groups justify the chosen concept of an anthropomorphic MIS robotic system which imitates the natural motion of the hands.

Motion prediction and control for patient motion compensation in radiotherapy

AbstractThis paper summarizes the work carried out at Coventry University on video tracking and patient motion compensation during the MAESTRO European project. A novel combination of motion prediction, couch control and couch nonlinearities compensation was developed and implemented in real time to control an Elekta AB (Publ) ‘Precise’ patient support system or ‘couch'. The reference trajectory was obtained from a video tracking system implemented using LabVIEW. A new anthropomorphic robotic system was used to generate target motions which were captured with a video tracking system that provided a reference to the PSS control system implemented using Matlab® Simulink® and dSPACE. The PSS with its new control system reduced the vertical and longitudinal motion of a surrogate marker located on a robotic arm to less than 1mm RMS and 2mm 95% confidence interval. The motion compensation resulted in significant dosimetric improvements compared to irradiating a moving target. Irradiation of Gafchromic films produced dose distributions with no noticeable differences between fixed target and a motion compensated moving target.

Learning impedance control of antagonistic systems based on stochastic optimization principles

Novel anthropomorphic robotic systems increasingly employ variable impedance actuation with a view to achieving robustness against uncertainty, superior agility and improved efficiency that are hallmarks of biological systems. Controlling and modulating impedance profiles such that they are optimally tuned to the controlled plant is crucial in realizing these benefits. In this work, we propose a methodology to generate optimal control commands for variable impedance actuators under a prescribed tradeoff of task accuracy and energy cost. We employ a supervised learning paradigm to acquire both the plant dynamics and its stochastic properties. This enables us to prescribe an optimal impedance and command profile (i) tuned to the hard-to-model plant noise characteristics and (ii) adaptable to systematic changes. To evaluate the scalability of our framework to real hardware, we designed and built a novel antagonistic series elastic actuator (SEA) characterized by a simple mechanical architecture and we ran several evaluations on a variety of reach and hold tasks. These results highlight, for the first time on real hardware, how impedance modulation profiles tuned to the plant dynamics emerge from the first principles of stochastic optimization, achieving clear performance gains over classical methods that ignore or are incapable of incorporating stochastic information.

System and software safety analysis for the ERA control computer

The European Robotic Arm (ERA) is a seven degrees of freedom relocatable anthropomorphic robotic manipulator system, to be used in manned space operation on the International Space Station, supporting the assembly and external servicing of the Russian segment. The safety design concept and implementation of the ERA is described, in particular with respect to the central computer's software design. A top–down analysis and specification process is used to down flow the safety aspects of the ERA system towards the subsystems, which are produced by a consortium of companies in many countries. The user requirements documents and the critical function list are the key documents in this process. Bottom–up analysis (FMECA) and test, on both subsystem and system level, are the basis for safety verification. A number of examples show the use of the approach and methods used.

Robonaut: NASA's space humanoid

To meet the dexterous manipulation needs of future missions, NASA is developing Robonaut, an astronaut-sized robot with two arms, two five-fingered hands, a head and a torso. Robonaut is advancing the state of the art in anthropomorphic robotic systems, dexterous robotic hands, modular robotic systems components and telepresence control systems.