A period-varying iterative learning control scheme is proposed for a robotic manipulator to learn a target trajectory that is planned by a human partner but unknown to the robot, which is a typical scenario in many applications. The proposed method updates the robot’s reference trajectory in an iterative manner to minimize the interaction force applied by the human. Although a repetitive human–robot

Micropositioning systems are widely employed in industrial applications. Nonminimum-phase (NMP) is a normal phenomenon in micropositioning system, which leads to a great challenge for control system design. Model predictive control (MPC) is effective in handling the NMP problem. However, the parameter tuning of MPC is quite complicated and time-consuming using traditional methods for motion tracking

Peg-in-hole assembly with narrow clearance is a typical robotic contact-rich task in industrial manufacturing. Robot learning allows robots to directly acquire the assembly skills for this task without modeling and recognizing the complex contact states. However, learning such skills is still challenging for robot because of the difficulties in collecting massive transitions data and transferring skills

Visual short-term tracking in a long sequence of images with a lot of pose variations, target deformations and different types of occlusion is one of the harshest tasks in image processing. Overcoming such challenges can be performed in a superior way by combining different trackers. In this paper, we propose a method that combines different algorithms for tracking the given target. The algorithms

In this paper an analytical stability criterion for linear haptic devices is determined, in the presence of the operator. The model of the haptic device and the virtual environment are assumed as mass-damper and spring-damper, respectively. Two different models for operator’s hand are assumed, and the stability boundaries are derived analytically. The main contribution of this paper is the analytical

For robot manipulation, reinforcement learning has provided an effective end to end approach in controlling the complicated dynamic system. Model-free reinforcement learning methods ignore the model of system dynamics and are limited to simple behavior control. By contrast, model-based methods can quickly reach optimal trajectory planning by building a dynamic system model. However, it is not easy

In this paper, an environment state perception method is proposed, in which the visual perception, point cloud process and knowledge representation are combined together to handle the perception problem of robot assembly tasks. Different from regular perception systems, objects in assembly workspace are required to be matched with corresponding models in database which records prior information related

Proceeding for an elucidating draft for the robot’s path planning, there are several aspects which need to be addressed and discuss in detail. Some key points include the definition of the working environment, type of technique used to solve a particular type of problem, their subclassification and interdependencies with each other. It is also required to discuss in detail to understand and solve the

In the design of robotic arms, structural topology optimization considering variable configurations with high computational efficiency is still a challenging issue. In this paper, the worst case identification based topology optimization of a 2-DoF hybrid robotic arm is accomplished, and the presented work mainly covers: (1) efficient worst case identification; (2) optimization problem construction

Stereo vision, structured light, and time of flight (ToF) are different range imaging techniques that acquire a scene and provide different features such as a depth map and an amplitude image. Compared to other imaging techniques, ToF can measure depth with high speed and good precision according to state of the art. However, it faces multipath interference (MPI) problems that give rise to an error

Most of the current human-aware navigation methods of service robots focus on improving the reactive navigation of local path planning without considering the global environment. A global path planning method is proposed based on the global scope of pedestrian perception and multi-layer cost-maps. Firstly, personal space and group interaction are modeled as social cost based on pedestrian perception

Minimally invasive transoral surgery (TROS) aims to reduce the trauma and complications, where transoral examination with an endoscope is a vital step. Close to the critical head-neck-brain anatomical structures, the transoral procedures can be much complicated and pose significant challenges to accurate navigation requirements. Therefore, it is laborious for navigating endoscopic instruments due to

Power lower limb exoskeleton has gained considerable interests since it is widely applied in both walking assistance and rehabilitation related applications. The most challenge problem of these kinds lower exoskeletons is how to deal with the complex environment, such as stairs in daily life. Based on a developed lower limb exoskeleton named AssItive DEvice for paRalyzed patients (AIDER), this paper

Robotics, and its hardware, since its development, is a rapidly expanding field of study. Hexapods are being used in many of the sophisticated applications. The hexapod designs and improvements in controller power have allowed these robots to be used in several different industries, including nuclear power, forestry, defence, automotive and others. The challenge that designers face, is the demand that

Robots with multiple degrees-of-freedom (DoFs) are being used in the surgical field more frequently over the last decade, not as an alternative but a main method for minimally invasive surgeries. Surgical robots allow surgeons to perform surgical procedures more steadily and more accurately. In this paper, a newly designed 6-DoF manipulator for minimally invasive scaphoid surgery is introduced with

The aerodynamic model of flexible wing aircraft is highly nonlinear with continuously time-varying dynamics under kinematic constraints. The nonlinearities stem from the aerodynamic forces and continuous deformations in the flexible wing. In spite of the various experimental attempts and theoretical setups that were made to model these dynamics, an accurate formulation was not achieved. The control

Radioembolization, a targeted treatment for advanced-stage liver cancer, is a medical procedure in which millions of radioactive microspheres (20–40 µm in diameter) are released into the blood vessels feeding liver tumors. These microspheres not only reduce blood flow to the tumors; their associated radiation kills the cancerous tissues into which they embed. While effective, this procedure also poses

This study proposes an integrated planning and control framework for achieving three-dimensional robust and dynamic legged locomotion over uneven terrain. The proposed framework is composed of three hierarchical layers. The high-level layer is a state-space motion planner designing highly dynamic locomotion behaviors based on a reduced-order robot model. This motion planner incorporates two robust

Simultaneous localization and mapping (SLAM) of an unknown environment is a primary requirement for any autonomous robot. In this paper we present a cost-effective, robust, and integrated software/hardware SLAM solution for 2D mapping of large indoor environments. The presented SLAM solution consists of a robotic platform, referred as MapperBot, and an effective implementation of SLAM algorithm, referred

Autonomous unmanned aerial systems (UAS) could supplement and eventually subsume a substantial portion of the mission set currently executed by remote pilots, making UAS more robust, responsive, and numerous than can be achieved by teleoperation alone. Unfortunately, the development of robust autonomous systems is difficult, costly, and time-consuming. Furthermore, the resulting systems often make

Robots have several applications in different fields of nowadays life as in sports training-assistance. One of these sports is Fencing that is an individual duel Olympic sport using a bladed weapon. A typical fencer’s training consists of practicing different techniques. This practice is achieved through three training approaches that are not best utilized due to some constraints referred to humans’

This paper presents an energetics analysis of a bi-modal vehicle that is capable of rolling and flying. The vehicle under consideration combines the mobility and maneuverability of rotary wing flight with the efficiency of rolling locomotion. The energetics analysis uses blade element momentum theory and an electromechanical motor model to predict the electrical power consumption of the propulsion

Deep Learning methods are gaining popularity with both academy and industry. We are in dire need of student affordable educational platform that can support doing Deep Learning experiments. In this paper, we present a mobile robot platform based on Arduino for educational experiments in visual Deep Learning. The educational robot uses Arduino open-source hardware and supports various programming interfaces

A kind of pitch channel dynamic model of hypersonic aircraft considered with both the model of engine and the model of elastic shape is studied. A special typical flying point is chosen that the state of elastic shape is assumed to be constant and the engine is designed with a PID law to make the speed of aircraft close to a constant. Then a kind of hybrid controller based on FLNN neural network and

Detecting interested targets on aerial robotic systems is a challenging task. Due to the long view distance of air-to-ground observation, the target size is small and the number is large in the scene. In addition, the target only occupies part of the image, and the complex background environment can easily cover the feature information of the target. In this paper, a novel target detection method based

Studies on hand motion recognition based on biosignals have become popular as such recognition can be applied to various input interfaces and motion measurements for human–robot/computer interaction. In recent years, many machine-learning-based technologies have been developed to analyze such biosignals more accurately. Among various possible biosignals, we focus on forearm deformation which is an

With the development of robotics, the application of robots has gradually evolved from industrial scenes to more intelligent service scenarios. For multitasking operations of robots in complex and uncertain environments, the traditional manual coding method is not only cumbersome but also unable to adapt to sudden changes in the environment. Imitation learning that avoids learning skills from scratch

Nonnegative matrix factorization (NMF) plays a significant role of finding parts-based representations of nonnegative data that is widely used in data analysis applications. However, sequential data (e.g., video scene, human action) with ordered structures usually share obvious similar features between neighboring data points unless a sudden change occurs, it is important to exploit temporal information

As a common athletics injury in orthopedics clinic, ankle injury may affect a person's daily life and ankle injury rehabilitation has gained increasing interests from the medical and robotic societies. A novel hybrid ankle rehabilitation robot is proposed, which composing of a serial and a parallel part. In order to analyze its kinematic performances, the parallel part of the robot is simplified as

This research presents a novel design metric based on maximum power flux density for the assessment of the severity of a transient physical contact between a robot manipulator and a human body region. Such incidental transient contact can occur in the course of a collaborative application of the power- and force-limiting type. The proposed metric is intended for the design and development of the robot

This paper develops an enhanced teaching interface tested on both a Baxter robot and a KUKA iiwa robot. Movements are collected from a human demonstrator by using a Kinect v2 sensor, and then the data is sent to a remote PC for the teleoperation with Baxter. Meanwhile, data is saved locally for the playback process of the Baxter. The dynamic movement primitive (DMP) is used to model and generalize

This paper proposes an architecture that explores a gap in the spectrum of existing strategies for robot control mode switching in adjustable autonomy. In situations where the environment is reasonably known and/or predictable, pre-planning these control changes could relieve robot operators of the additional task of deciding when and how to switch. Such a strategy provides a clear division of labour

A reliable, real time localization functionality is crutial for actively controlled capsule endoscopy robots, which are an emerging, minimally invasive diagnostic and therapeutic technology for the gastrointestinal (GI) tract. In this study, we extend the success of deep learning approaches from various research fields to the problem of sensor fusion for endoscopic capsule robots. We propose a multi-sensor

Since the development of capsule endoscopy technology, medical device companies and research groups have made significant progress to turn passive capsule endoscopes into robotic active capsule endoscopes. However, the use of robotic capsules in endoscopy still has some challenges. One such challenge is the precise localization of the actively controlled robot in real-time. In this paper, we propose

This paper presents a method to localize a robot in a global coordinate frame based on a sparse 2D map containing outlines of building and road network information and no location prior information. Its input is a single 3D laser scan of the surroundings of the robot. The approach extends the generic chamfer matching template matching technique from image processing by including visibility analysis

Currently a telerehabilitation system includes a therapist and a patient where the therapist interacts with the patient, typically via a verbal and visual communication, for assessment and supervision of rehabilitation interventions. This mechanism often fails to provide physical assistance, which is a modus operandi during physical therapy or occupational therapy. Incorporating an actuation modality

This paper presents a walking pattern detection method for a smart rollator. The method detects the rollator user's lower extremities from the depth data of an RGB-D camera. It then segments the 3D point data of the lower extremities into the leg and foot data points, from which a skeletal system with 6 skeletal points and 4 rods is extracted and used to represent a walking gait. A gait feature, comprising