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

Since the last few decades, research in the area of robotics technology has been emphasizing in the modeling and development of cognitive machines. A cognitive machine can have multiple cognitive capabilities to be programmed to make it artificially intelligent. Numerous cognitive modules interact to mimic human behavior in machines and result in such a heavily coupled system that a minor change in

The universal Turing Machine (TM) is a model for Von Neumann computers — general-purpose computers. A human brain, linked with its biological body, can inside-skull-autonomously learn a universal TM so that he acts as a general-purpose computer and writes a computer program for any practical purposes. It is unknown whether a robot can accomplish the same. This theoretical work shows how the Developmental

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

In the past several years, grasp analysis of multi-fingered robotic hands has been actively studied through the use of posture synergies. In these grasping planning algorithms, a formulated optimization is usually performed in the hand’s low-dimensional representation together with the hand’s position and orientation. The optimization terminates at a stable grasp, often after repeated trials with different

This paper describes a rule base-Sugeno fuzzy hybrid controller for path planning of single as well as multiple humanoid robots in cluttered environments. Initially, sensor outputs regarding the obstacle distances are used as inputs to the rule base model, and turning angle is obtained as the output. The rule-based analysis is used for training the fuzzy controller with membership functions. The output

The prime challenge in a humanoid robot is its stability on two feet due to the presence of an underactuated system. In this paper, the complete dynamics of the humanoid robot has been described in essence of torque calculation at the end effectors. Presence of various restraints in humanoid robot motion makes the task of stabilization an even humongous one. Therefore, to neutralize these constraints

Humanoid robots are often supposed to share their workspace with humans and thus have to deal with objects used by humans in their everyday life. In this article, we present our novel approach to humanoid navigation through cluttered environments, which exploits knowledge about different obstacle classes to decide how to deal with obstacles and select appropriate robot actions. To classify objects

Exoskeleton for motion assistance has obtained more and more attention due to its advantages in rehabilitation and assistance for daily life. This research designed an estimation method of human joint torque by the kinetic human–machine interaction between the operator’s elbow joint torque and the output of exoskeleton. The human elbow joint torque estimation was obtained by back propagation (BP) neural

This paper contributes toward the benchmarking of control architectures for bipedal robot locomotion. It considers architectures that are based on the Divergent Component of Motion (DCM) and composed of three main layers: trajectory optimization, simplified model control, and whole-body quadratic programming (QP) control layer. While the first two layers use simplified robot models, the whole-body

We developed a bipedal robot equipped with brake and clutch mechanisms to change the number of active and passive joints, thereby enabling various types of movements including normal active walking using 12-dof joints, under-actuated walking using brake, and passive-based walking using clutch and passive joints. In this paper, we describe three technologies to achieve the proposed system and show experimental

The human hand is a complex, highly-articulated system, which has been the source of inspiration in designing humanoid robotic and prosthetic hands. Understanding the functionality of the human hand is crucial for the design, efficient control and transfer of human versatility and dexterity to such anthropomorphic robotic hands. Although research in this area has made significant advances, the synthesis

Although there are several popular and capable humanoid robot designs available in the kid-size range, they lack some important characteristics: affordability, being user-friendly, using a wide-angle camera, sufficient computational resources for advanced AI algorithms, and mechanical robustness and stability are the most important ones. Recent advances in 3D printer technology enables researchers

A three-finger under actuated robotic hand with dexterous force control and inherent compliance is developed and tested. A simplified biomimetic finger design is generated and applied with mechanical intelligence principles carefully designed and embedded such that optimal trajectories for grabbing are naturally followed and the fingers can automatically conform to the goal object. A generalizable

Unsteady locomotion and the dynamic environment are two problems that block humanoid robots to apply visual Simultaneous Localization and Mapping (SLAM) approaches. Humans are often considered as moving obstacles and targets in humanoid robots working space. Thus, in this paper, we propose a robust dense RGB-D SLAM approach for the humanoid robots working in the dynamic human environments. To deal

Gait development for bipedal/humanoid robots has been a field of study with a lot of attention for several years and is becoming increasingly important as robots slowly become part of our daily lives. Therefore, it is expectable that robots should adopt human-like behaviors in order to make their interactions with humans more natural and studies have been made involving robots that have a natural,

This paper presents a balance-centered planner for object re-posing. It uses Center-of-Mass (CoM) constraints to preserve robot stability and provides stable, IK-feasible, and collision-free upper-body poses, allowing the robot to complete dexterous object manipulation tasks with different objects. The technical contributions of the planner are two-fold. First, it evaluates the robot stability margin

This paper describes the procedure followed for using third-party tools and applications, avoiding the development of complex communication software modules for data sharing. A common practice in robotics is the use of middlewares to interconnect different software applications, hardware components, or even complete systems. It allows code and tool reuse minimizing the development effort. In this way

Real-time human intent recognition is important for controlling low-limb wearable robots. In this paper, to achieve continuous and precise recognition results on different terrains, we propose a real-time training and recognition method for six locomotion modes including standing, level ground walking, ramp ascending, ramp descending, stair ascending and stair descending. A locomotion recognition system

Biped humanoid robots that operate in real-world environments need to be able to physically recognize different floors to best adapt their gait. In this work, we describe the preparation of a dataset of contact forces obtained with eight force tactile sensors for determining the underlying surface of a walking robot. The data is acquired for four floors with different coefficient of friction, and different

Most existing motion control methods for humanoids aim at avoiding falling. However, the humanoid is generally an unstable system that cannot completely avoid falling and it is difficult to cope with the sudden fall of a robot. This paper designs a planning method of fall protection for humanoids according to the human falling motion. This method changes the impact position between the robot and ground

This paper proposes a new framework to generate 3D multi-contact locomotion with low computation cost. The proposed framework consists of (a) the derivation of the prospect centroidal dynamics by introducing a force distribution ratio, where it can be represented with a formulation similar to the inverted pendulum’s one, and (b) the development of a fast computation method for generating a 3D center-of-mass

This work introduces a new sensing system for biped robots based on plantar robot skin, which provides not only the resultant forces applied on the ankles but a precise shape of the pressure distribution in the sole together with other extra sensing modalities (temperature, pre-touch and acceleration). The information provided by the plantar robot skin can be used to compute the center of pressure

Stable bipedal walking is a key prerequisite for humanoid robots to reach their potential of being versatile helpers in our everyday environments. Bipedal walking is, however, a complex motion that requires the coordination of many degrees of freedom while it is also inherently unstable and sensitive to disturbances. The balance of a walking biped has to be constantly maintained. The most effective

Intelligent assistive robots can potentially contribute to maintaining an elderly person’s independence by supporting everyday life activities. However, the number of different and personalized activities to be supported renders pre-programming of all respective robot behaviors prohibitively difficult. Instead, to cope with a continuous and potentially open-ended stream of cooperative tasks, new collaborative

This paper addresses the problem of obtaining the required motions for a humanoid robot to perform grasp actions trying to mimic the coordinated hand–arm movements humans do. The first step is the data acquisition and analysis, which consists in capturing human movements while grasping several everyday objects (covering four possible grasp types), mapping them to the robot and computing the hand motion

Bipedal walking is a complex phenomenon that is not fully understood. Simplified models make it easier to highlight the important features. Here, the variable length inverted pendulum (VLIP) model is used, which has the particularity of taking into account the vertical oscillations of the center of mass (CoM). When the desired walking gait is defined as virtual constraints, i.e., as functions of a

This paper presents a control scheme for the humanoid robot TEO’s elbow joint based on a novel tuning method for fractional-order PD and PI controllers. Due to the graphical nature of the proposed method, a few basic operations are enough to tune the controllers, offering very competitive results compared to classic methods. The experiments show a robust performance of the system to mass changes at

Grasp planning and motion synthesis for dexterous manipulation tasks are traditionally done given a pre-existing kinematic model for the robotic hand. In this paper, we introduce a framework for automatically designing hand topologies best suited for manipulation tasks given high-level objectives as input. Our pipeline is capable of building custom hand designs around specific manipulation tasks based

There has been great progress in soft robot design, manufacture, and control in recent years, and soft robots are a tool of choice for safe and robust handling of objects in conditions of uncertainty. Still, dexterous in-hand manipulation using soft robots remains a challenge. This paper introduces foam robot hands actuated by tendons sewn through a fabric glove. The flexibility of tendon actuation

In this paper, we propose a locomotion planning framework for a humanoid robot with stable whole-body collision avoidance motion, which enables the robot to traverse an unknown narrow space on the spot based on environmental measurements. The key idea of the proposed method is to reduce a large computational cost for the whole-body locomotion planning by utilizing global footstep planning results and

Robot performance measures are important tools for quantifying the ability to carry out manipulation tasks. Generally, these measures examine the system’s kinematic transformations from configuration to task space. This means that environmental constraints are neglected in spite of the significant effects they may have on the robot’s admissible motions. In this paper, we propose a new measure called

Robots might not act according to human expectations if they cannot anticipate how people make sense of a situation and what behavior they consider appropriate in some given circumstances. In many cases, understanding, expectations and behavior are constrained, if not driven, by culture, and a robot that knows about human culture could improve the quality level of human–robot interaction. Can we share

External force observer for humanoid robots has been widely studied in the literature. However, most of the proposed approaches generally rely on information from six-axis force/torque sensors, which the small or medium-sized humanoid robots usually do not have. As a result, those approaches cannot be applied to this category of humanoid robots, which are widely used nowadays in education or research

We evaluate the ability of locally present participants to localize an avatar head’s gaze direction rapidly in hosted telepresence. We performed a controlled user study to test two potential solutions to indicate a remote user’s gaze. We analyze the influence of the user’s distance to the avatar and display technique on localization accuracy. Furthermore, we examine the effect of the avatar head’s

This paper presents an extension of previous model predictive control (MPC) schemes for dynamic walking to the stabilization of the time-varying divergent component-of-motion (DCM). In order to address the control authority limitations caused by fixed footholds, the step positions and rotations are treated as control inputs, allowing the generation and execution of stable walking motions, both at high

Robotic exoskeletons are expected to show high compliance and low impedance for human–robot interactions (HRIs). Our study introduces a novel method based on nonlinear model reference adaptive control (MRAC) to reduce the inherent impedance and replace the traditional impedance controller in HRIs. The control law and adaptive law are designed according to a candidate Lyapunov function. A simple system

This paper presents a general framework for locomotion control and generation of humanoid robots. Different from most of the existing work which uses the zero-moment point (2mp) to determine the feasibility of robot’s motion, we use the so-called contact wrench cone to derive motion feasibility conditions, whole-body motion controllers, and locomotion generators. The contact wrench cone consists of

In this paper, we propose standing and stepping control with switching rules based on angular momentum around the ankle for planar bipedal robots. A theoretical analysis under some approximation and mass distribution conditions shows that the proposed standing control maximizes stable regions. We can then classify the state of robots into the following three categories: (1) stabilizable via ankle torque;

This paper proposes an external force detection method for humanoid robot arm without using joint torque sensors, which can detect the external force of the joint space in real time during the operation of the robot. We first analyzed the structure of the humanoid robot arm we designed, and then established the external force detection model of the robot arm based on robot dynamics and motor dynamics

The proper description of finger-object contact state is critical to the analysis and control of multi-fingered hand grasping. At present, most studies assume that the finger-object contact state is invariable. However, in different stages of hand grasping, finger-object contact state is usually variable due to different contact factors, therefore, current finger-object contact models are not very

Among the possible fields in human society in which robotics can be applied, the possibility of a robotic guard has been imagined since long time. Human guards usually perform a range of tasks in which a robot can provide help. Security personnel not only perform security tasks and patrolling services, but also have to interact with people, providing additional information about the area they safeguard

The tactile sensing is of significant interest for coexisting-cooperative-cognitive robots (Tri-Co robots). In order to improve the tactile sensing performance of the robot via an electronic skin (e-skin), an auxiliary elastomeric substrate is required. This paper investigates the effect of the substrate including elastic modulus, thickness and location on the static sensing at first. It is found that

This study aimed to propose an extended state observer fuzzy-approximation-based active disturbances rejection control (FAADRC) method for a dual-arm humanoid robotic system. The purpose of this control system was to provide disturbance estimation and compensation to enable the humanoid robots to track any continuous desired trajectory, even in the presence of environmental disturbances and parametric

Technological advances in robotic hardware and software have enabled powered exoskeletons to move from science fiction to the real world. The objective of this article is to emphasize two main points for future research. First, the design of future devices could be improved by exploiting biomechanical principles of animal locomotion. Two goals in exoskeleton research could particularly benefit from

Epilepsy is caused by sudden abnormal discharges of neurons in the brain. This paper constructs an automatic seizure detection system, which combines the predicting result of multi-domain feature with the predicting result of spike rate feature to detect the occurrence of epileptic seizures. After segmenting EEG data into 5s with 80% overlap epochs, the paper extracts time domain features, frequency

The channel numbers and electrode layouts are usually determined empirically that would reduce robustness when acquiring surface electromyography (EMG) signals for prosthetic hand systems. It is necessary to study how they can be exploited effectively for a more accurate extraction. In response to the problem, an experiment is designed that establishes the relationship between sEMG signals and forearm

Motion detection and object tracking play important roles in unsupervised human–machine interaction systems. Nevertheless, the human–machine interaction would become invalid when the system fails to detect the scene objects correctly due to occlusion and limited field of view. Thus, robust long-term tracking of scene objects is vital. In this paper, we present a 3D motion detection and long-term tracking

Human pose estimation is a fundamental but challenging task in computer vision. The estimation of human pose mainly depends on the global information of the keypoint type and the local information of the keypoint location. However, the consistency of the cascading process makes it difficult for each stacking network to form a differentiation and collaboration mechanism. In order to solve these problems

Facial expression recognition has been widely used in human computer interaction (HCI) systems. Over the years, researchers have proposed different feature descriptors, implemented different classification methods, and carried out a number of experiments on various datasets for automatic facial expression recognition. However, most of them used 2D static images or 2D video sequences for the recognition

Electromyography (EMG) has been widely accepted to interact with prosthetic hands, but still limited to using few channels for the control of few degrees of freedom. The use of more channels can improve the controllability, but it also increases system’s complexity and reduces its wearability. It is yet clear if optimizely placing the EMG channel could provide a feasible solution to this challenge

Due to the extremely weak intensity of the biomagnetic field and the serious interference from the environmental magnetic field, the detection of the biomagnetic field becomes such challenging work. After analyzing the deficiencies in the current biomagnetic field sensors, this paper proposes and realizes a high-sensitivity magnetic field sensor, based on the giant magneto-impedance (GMI) effect. Taking

Localization of vessel Region of Interest (ROI) from medical images provides an interactive approach that can assist doctors in evaluating carotid artery diseases. Accurate vessel detection is a prerequisite for the following procedures, like wall segmentation, plaque identification and 3D reconstruction. Deep learning models such as CNN have been widely used in medical image processing, and achieve

Surface electromyography (sEMG) signals have been widely used in human–machine interaction, providing more nature control expedience for external devices. However, due to the instability of sEMG, it is hard to extract consistent sEMG patterns for motion recognition. This paper proposes a dual-flow network to extract the temporal-spatial feature of sEMG for gesture recognition. The proposed network

Aggressive driving, such as frequent lane changes, endangers other persons or property but is challenging to be continuously tracked by existing traffic surveillance systems. In this paper, we use wrist-mounted wearables, such as a smartwatch to monitor the driver’s forearm acceleration and to detect lane changes. Because the forearm acceleration of lane changes can be significantly affected by traveling

The corticomuscular coupling (CMC) characterization between the motor cortex and muscles during motion control is a valid biomarker of motor system function after stroke, which can improve clinical decision-making. However, traditional CMC analysis is mainly based on the coherence method that can’t determine the coupling direction, whereas Granger Causality (GC) is limited in identifying linear cause–effect

Crowd feature perception is an essential step for us to understand the crowd behavior. However, as the individuals present not only the sociality but also the randomness, there remain great challenges to extract the sociality of the individual directly. In this paper, we propose a crowd feature perception algorithm based on a sparse linear model (SLM). It builds the statistical characterization of

This paper details an intelligent motion planning and control approach for a one-degree of freedom joint of a robotic arm that can be used to implement anthropomorphic robotic hands. This intelligent control method is based on bio-inspired electronic neural networks and contractile artificial muscles implemented with shape memory alloy (SMA) actuators. The spiking neural network (SNN) includes several

Deep learning (DL) has made tremendous contributions to image processing. Recently, the DL has also attracted attention in the specialized field of neural decoding from raw myoelectric signals (electromyograms, EMGs). However, to our knowledge, most existing methods require some measure of preprocessing of the raw EMGs. Moreover, research to date has not accounted for the variability in the signal

Re-planning of gait trajectory is a crucial ability to compensate for external disturbances. To date, a large number of methods for re-planning footsteps and timing have been proposed. However, robots with the ability to change gait from walking to running or from walking to hopping were never proposed. In this paper, we propose a method for re-planning not only for footsteps and timing but also for