It has been established that the transfer of human adaptive impedance is great significance for physical human-robot interaction (pHRI). By processing electromyography (EMG) signals collected from muscles, limb could be extracted and transferred to robots. The existing interfaces rely only on visual feedback and, thus, may insufficient skill in a sophisticated environment. In this paper, haptic mechanism introduced result muscle activity would generate EMG natural manner, order achieve...

One promising approach for robots efficiently learning skills is to learn manipulation from human tutors by demonstration and then generalize these learned complete new tasks. Traditional generalization methods, however, have not well considered impedance features, which makes the less humanlike restricted in physical human-robot interaction scenarios. In particular, stiffness has been considered. This paper develops a framework that enables robot both movement features tutor. To this end,...

Robots are often required to generalize the skills learned from human demonstrations fulfil new task requirements. However, skill generalization will be difficult realize when facing with following situations: for a complex multistep includes number of features; some special constraints imposed on robots during process reproduction; and completely situation quite different one in which given robot. This work proposes framework facilitate robot generalization. The basic idea lies that first...

The integration of advanced sensor technologies has significantly propelled the dynamic development robotics, thus inaugurating a new era in automation and artificial intelligence. Given rapid advancements robotics technology, its core area—robot control technology—has attracted increasing attention. Notably, sensors fusion technologies, which are considered essential for enhancing robot have been widely successfully applied field robotics. Therefore, techniques with enables adaptation to...

Multifingered hand dexterous manipulation is quite challenging in the domain of robotics. One remaining issue how to achieve compliant behaviors. In this work, we propose a human-in-the-loop learning-control approach for acquiring grasping and skills multifinger robot hand. This takes depth image human as input generates desired force commands robot. The markerless vision-based teleoperation system used task demonstration, an end-to-end neural network model (i.e., TeachNet) trained map pose...

Contact-rich manipulation tasks are difficult to program be performed by robots. Traditional compliance control methods, such as impedance control, rely excessively on environmental models and ineffective in the face of increasingly complex contact tasks. Reinforcement learning (RL) has now achieved great success fields games robotics. Autonomous skills can empower robots with autonomous decision-making capabilities. To this end, work introduces a novel framework that combines deep RL (DRL)...

Harvesting robots had difficulty extracting filament phenotypes for small, numerous filaments, heavy cross-obscuration, and similar phenotypic characteristics with organs. Robots experience in localizing under near-colored backgrounds fuzzy contour features. It cannot accurately harvest filaments robots. Therefore, a method detecting locating picking points based on an improved DeepLabv3+ algorithm is proposed this study. A lightweight network structure, ShuffletNetV2, was used to replace...

Using the first-principles molecular dynamics simulations and CI-NEB calculations, we performed a systematic comprehensive investigation on chemical compatibility of various solvents (carbonate esters, aromatic solvents, ethers, carboxylic water, DMSO ionic liquids) electrolytes (DMC-Al(OTF)3, DME-Al(OTF)3, GBL-Al(OTF)3, H2O-Al2(SO4)3, DMSO-Al(OTF)3, [EMIm]+Cl--[AlCl3] urea-AlCl3) with Mo2TiC2-based MXenes, evaluating their possible use as additives in aluminum-ion batteries (AIBs). Among...

Abstract Nowadays, AL/CFRP laminates are widely used in the fuselage structures of medium‐ to large‐sized aircraft due their excellent performance, particularly enhancing stiffness and strength wings. However, delamination at interface can easily occur, limiting performance. A unique design strategy is proposed help fibers enter surface microstructure grooves. varied component interfaces have microstructures. Short beam tests compare failure mechanisms load‐bearing capacities with diverse...

How to enable robotic compliant manipulation has become a critical problem in the robotics field. Inspired by biomimetic adaptive control strategy, this article presents novel representation model named human-like movement primitives (Hl-CMPs) which could allow robot learn behaviors. The state-of-the-art approaches can hardly complete profiles for specific task. Comparatively, our encode task-specific parametric trajectories, correspondingly associated with dynamic trajectories including...

Robotic compliant manipulation is a very challenging but urgent research spot in the domain of robotics. One difficulty lies lack unified representation for encoding and learning profiles. This article aims to introduce novel control framework address this problem: 1) we provide parametric that enables skill be encoded space allows robot learn skills based on motion force information collected from human demonstrations; 2) updating laws profiles, including impedance are derived biomimetic...

Robotic rigid contact-rich manipulation in an unstructured dynamic environment requires effective resolution for smart manufacturing. As the most common use case intelligence industry, a lot of studies based on reinforcement learning (RL) algorithms have been conducted to improve performances single peg-in-hole assembly. However, existing RL methods are difficult apply multiple issues due more complicated geometric and physical constraints. In addition, previously limited solutions assembly...

The accurate acquisition of safflower filament information is the prerequisite for robotic picking operations. To detect filaments accurately in different illumination, branch and leaf occlusion, weather conditions, an improved Faster R-CNN model was proposed. Due to characteristics being dense small images, selected ResNeSt-101 with residual network structure as backbone feature extraction enhance expressive power extracted features. Then, using Region Interest (ROI) Align ROI Pooling...

Purpose Teaching by demonstration (TbD) is a promising way for robot learning skills in human and collaborative hybrid manufacturing lines. Traditionally, TbD systems have only concentrated on how to enable robots learn movement from humans. This paper aims develop an extended system which can also stiffness regulation strategies Design/methodology/approach Here, the authors propose dynamical motor primitives (DMP) framework achieve this goal. In addition advantages of traditional ones,...

Learning a task such as pushing something, where the constraints of both position and force have to be satisfied, is usually difficult for collaborative robot. In this work, we propose multimodal teaching-by-demonstration system which can enable robot perform kind tasks. The basic idea transfer adaptation multi-modal information from human tutor by taking account multiple sensor signals (i.e., motion trajectories, stiffness, profiles). tutor's stiffness estimated based on limb surface...

The coupling reaction of carbon dioxide (CO2) and epoxides is one the most efficient pathways to achieve balance. However, accomplish it under mild conditions, especially atmospheric pressure, still a perplexing problem. Three novel ionic liquids (ILs), [DMAPBrPC][TMGH], [DMAPBrPC][DBUH], [DMAPBrPC][BTMA], are designed synthesized. All them display excellent catalytic activity for title achieving yield over 96.6% CO2 pressure at 60 °C. Interestingly, [DMAPBrPC][BTMA] with inert hydrogen atom...

One promising function of interactive robots is to provide a specific interaction force human users. For example, rehabilitation are expected promote patients' recovery by interacting with them prescribed force. However, motion uncertainties different individuals, which hard predict due the varying speed and noises during motion, degrade performance existing control methods. This paper proposes method learn desired reference trajectory for robot based on dynamic primitives (DMPs) iterative...

Robotic dual-arm manipulation often requires close cooperation between the arms. Dual-arm tasks are always difficult to program in advance, and then, executed autonomously by robots. Learning from demonstration is an efficient programming method for robots that can transfer human skills However, conventional skill learning methods, e.g., dynamic movement primitives (DMPs) only characterize motion information of each dimension independently, cannot take into account relationship...

In this paper, we present a method for robot to learn point-to-point motions from human demonstrations. The motion is modelled as nonlinear dynamic system called movement primitive (DMP). original DMP can be only used single demonstration. order multiple demonstrations of specific task, combine the with Gaussian mixture models (GMMs), and part learned through regression (GMR). Thus more features same skill extracted generate better motion, good performance DMP, e.g., ability generalization,...