21 accepted papers
Learning from Demonstrations (LfD) has emerged as a prominent paradigm for imparting motion skills to robotic systems. Dynamical systems (DS) offer a potent mathematical framework for representing point-to-point motions, a critical requirement for numerous practical applications in robotics. While e…
Wearable exoskeletons can augment human strength and reduce muscle fatigue during specific tasks. However, developing personalized and task-generalizable assistance algorithms remains a critical challenge. To address this, a meta-imitation learning approach is proposed. This approach leverages a tas
Hand exoskeletons have become increasingly crucial for the rehabilitation of hand function, as relevant studies have shown that using the exoskeletons to assist in rehabilitation training can improve hand motor function. However, developing a human-robot kinematic compatibility exoskeleton while pro
Current hand exoskeleton interaction methods primarily focus on recognizing a limited range of hand motion intentions and rely on pre-programmed control to execute predefined commands. However, these approaches face significant limitations when confronted with unanticipated or non-predefined scenari
Point-to-point and periodic motions are ubiquitous in the world of robotics. To master these motions, Autonomous Dynamic System (ADS) based algorithms are fundamental in the domain of Learning from Demonstration (LfD). However, these algorithms face the significant challenge of balancing precision i
This paper presents a novel voluntary control method for a hand assistive exoskeleton, leveraging an sEMG-driven musculoskeletal model to improve the performance of grasping tasks. To address the challenge of inadequate personalization in current hand exoskeleton assistance strategies, this research
Flexible sensors for joint angle measurement play a crucial role in various human-robot interaction applications. In previous studies, sensors with various sensing mechanisms have been developed. Among them, optical waveguide sensors exhibit high resistance to environmental factors (such as temperat…
Autonomous Dynamic System (DS)-based algorithms hold a pivotal and foundational role in the field of Learning from Demonstration (LfD). Nevertheless, they confront the formidable challenge of striking a delicate balance between achieving precision in learning and ensuring the overall stability of th…
Tactile sensors based on optical waveguides are highly sensitive to pressure, possess good chemical inertness and electromagnetic resistance, and are unaffected by temperature changes in the surrounding environment. Researchers have developed various waveguide structures with multi-level cores to si…
This letter proposes a robust stochastic differential equation approach for learning point-to-point motions in an adversarial way. The proposed stochastic dynamical model combines the advantages of the stochastic differential equation and the transformer-like function together to achieve both robust
The integral flexible tail has the potential advantage of lifelike undulating motion. However, due to the complex manufacturing process and difficult modification of structural parameters, its application in robotic fish encounters many challenges. Combining rigid structure and flexible material, th
This letter proposes a dynamic system approach to learn point-to-point motions while keeping the stability of the dynamic system. The proposed approach is grounded on a Learning from Demonstration (LfD) method based on a neural network, which gets a better reproduction performance while guaranteeing
Pre-trained multilingual language models play an important role in cross-lingual natural language understanding tasks. However, existing methods did not focus on learning the semantic structure of representation, and thus could not optimize their performance. In this paper, we propose Multi-level Mu…
Recent approaches for 3D object detection have made tremendous progresses due to the development of deep learning. However, previous researches are mostly based on individual frames, leading to limited exploitation of information between frames. In this paper, we attempt to leverage the temporal inf…
This paper proposes an offline and runtime combined framework for the autonomous motion of snake robots. With the dynamic feedback of its state during runtime, the robot utilizes the linear regression to update its control parameters for better performance and thus adaptively reacts to the environme…
This paper proposed an adaptive neural admittance control strategy for collision avoidance in human-robot collaborative tasks. In order to ensure that the robot end-effector can avoid collisions with surroundings, robot should be operated compliantly by human within a constrained task space. An impe…
This paper introduces an end-to-end learning approach based on Reward-modulated Spike-Timing-Dependent Plasticity (R-STDP) for a multi-layered spiking neural network (SNN). As a case study, a snake-like robot is used as an agent to perform target tracking tasks on the basis of our proposed approach.…
In this paper, a lightweight central pattern generator(CPG) model is designed for a snake-like robot, to achieve smooth transition of body shape and locomotion speed. First, based on the convergence behavior of the gradient system, a lightweight CPG model with fast computing time is designed and com…
In this paper, we design and build a power line inspection robot capable of hybrid operation modes. Specifically, the developed robot is able to land on the overhead ground wire (OGW) and to move as the climbing robot. When to negotiate obstacles, it can vertically take off the wire and fly over the…
In this paper, a biologically inspired 3D slithering gait for a snake-like robot is designed and implemented for the purpose of target tracking. First, by balancing the forward speed and the stability of the robot, a straight slithering gait is modelled, under which the robot can march straight, fas…
In this paper, a human robot shared control strategy is developed and tested on a Baxter robot. Using the proposed method, the human operator only needs to consider the motion of the end-effector of the manipulator, while the manipulator will avoid obstacle by itself without sacrificing the end effe…