In order to improve the working performance of the mining excavators, a new type of hydraulic excavator working device is proposed. The proposed excavator working device possesses main advantages of the Tri-Power structure, whereas the kinematic and dynamic analysis can be greatly simplified. In this paper, the kinematic model and tool force model of the new working device are established, and the

In this paper, a new haptic interaction is presented where the operator is in contact with the haptic device (HD) only when she/he is in contact with the virtual environment (VE). This is in contrast with traditional haptic systems, where the operator is always in contact with the HD, even if she/he is out of the VE. In this haptic interaction, a visual tracking system is used to track the operator’s

In this paper, a type-2 fuzzy PID controller is presented to improve position control and damp the oscillation of the load for overhead crane systems. As an extension of traditional fuzzy logic theory, type-2 fuzzy logic theory can effectively improve the control performance especially for internal and external disturbances systems. According to the dynamic and inherent under-actuated characteristics

Industrial robots are increasingly used in highly flexible interaction tasks, where the intrinsic variability makes difficult to pre-program the manipulator for all the different scenarios. In such applications, interaction environments are commonly (partially) unknown to the robot, requiring the implemented controllers to take in charge for the stability of the interaction. While standard controllers

In this manuscript, a recurrent neural network is proposed for variable admittance control in human–robot cooperation tasks. The virtual damping and the virtual inertia of the designed robot’s admittance controller are adjusted online and simultaneously. A Jordan recurrent neural network is designed and trained for this purpose. The network is indirectly trained using the real-time recurrent learning

Intelligent physical skills are a fundamental element needed by robots to interact with the real world. Instead of learning from individual sources in single cases, continuous robot learning from crowdsourced mentors over long terms provides a practical path towards realizing ubiquitous robot physical intelligence. The mentors can be human drivers that teleoperate robots when their intelligence is

In this paper, a B-spline chained multiple random matrix models (RMMs) representation is proposed to model geometric characteristics of an elongated deformable object. The hyper degrees of freedom structure of the elongated deformable object make its shape estimation challenging. Based on the likelihood function of the proposed B-spline chained multiple RMMs, an expectation-maximization (EM) method

Following rapidly and precisely a moving target has become the core functionality in robotic systems for transportation, manufacturing, and medical devices. Among existing targeting following methods, vision-based tracking continues to thrive as one of the most popular, and is the closest method to human perception. However, the low sampling rate and the time delays of visual outputs fundamentally

This decade has witnessed a paradigm shift in human-labor based rescue-surveillance operations. Research propositions have explored the possibility of replacing manual intervention for the management of catastrophic situations by a team of robots. However, to implement the concept into practice, the robotics community has faced several challenges. The multi-robotic system has to be duly coordinated

Parallel robots with R-(SS)2 (R, actuated revolute joint; S, spherical joint) branches are widely used in high-speed sorting. This kind of robot has been developed into a variety of robots with different moving platforms, but the error model is usually only applicable to the specific features of the moving platform. Thus, an adaptable error modeling method is in need. To solve this problem, this paper

Roads undergo rapid deterioration due to various economic, social and natural reasons. The uncertainty and unavailability of road safety information has become a major issue in reliably transporting goods, movement of heavy machinery, transport of people and materials to/from disaster areas and in even giving plain guarantees for safe traversability of a road that is good on paper. In this paper, we

A circular steering propulsion mechanism is proposed to explore autonomous movement of a miniature micro-vehicle with singular off-center nanoengine. The micro-vehicle comprising of gold, nickel, and platinum is invented and synthesized by layer-by-layer deposition based on the micro-electro-mechanical systems technology. The self-steering propulsion of the gold–nickel–platinum micro-vehicle is characterized

This paper aims to develop a background subtraction algorithm based on Gaussian Mixture Model (GMM) using Probability Density Function (PDF) to identify the location of moving objects over a belt conveyor for pick and place operations using an industrial robot. In the present work, a stationary webcam is placed above the conveyor system to capture images of the objects that are coming into the view

In past many researchers have designed the multiple robots which served as per the need of humans but unfortunately they are much expensive. It has been observed that man power is needed in the shopping marts especially on highway based stores and marts. Where it is found to be inconvenient for persons or owners to perform the duties all the time. This paper is centered around one of the best solution

The purpose of this article is twofold, one is to provide a brief review on various lavatory cleaning devices while the other is to study the feasibility of using these devices in public toilets in developing countries. The article presents a literature review on various lavatory cleaning devices, focusing on various designs available as patent documents and commercially available toilet cleaning robots

In this project, machine learning based techniques for real time terrain identification of the autonomous robots are investigated. The factors affecting the performance of autonomous robots include nature of trajectories, on-course obstacles, and nature of terrain. The challenges involved in understanding the terrain of autonomous robots are called localization problems. This project investigates a

Crack is the most common defect in the railway sleeper inspection work. However, it is still lack of effective algorithms to automatically detect. Two deep learning based methods were popularly used to detect cracks: two-stage methods and one-stage methods. However, they both have their corresponding shortcomings: for the two-stage methods, they are too slow; for the one-stage methods, their accuracy

The development and testing of a soft rotary actuator for gesture-based control is described in this paper. The soft rotary actuators are fabricated via a molding process and connected to a rotary joint as an antagonist and agonist pair, which gives rise to the clockwise and counter-clockwise rotation of the joint. The range of movement of the soft rotary actuator is 0°–90° for positive pressure actuation

Motion planning for inserting pegs remains an open problem. The difficulty lies in both the inevitable errors in the grasps of a robotic hand and absolute position errors in serial robotic manipulators. This paper proposes an integral method to solve the problem. The method uses combined task and motion planning to generate grasps and motions for a dual-arm robot to pick up objects and move them to

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

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 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

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 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

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

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’

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

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

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

In urban search and rescue domains, robots explore the affected terrain to search and assist disaster victims. RoboCup Rescue simulation provides a platform for disaster management where heterogeneous field agents (fire-brigade agent, ambulance agent, and police force agent) collaborate to manage a mimicked calamity situation. The role of police force agents is crucial, as they clear the blocked roads

In this paper, we present a bilevel optimal motion planning (BOMP) model for autonomous parking. The BOMP model treats motion planning as an optimal control problem, in which the upper level is designed for vehicle nonlinear dynamics, and the lower level is for geometry collision-free constraints. The significant feature of the BOMP model is that the lower level is a linear programming problem that

Intelligent service robot is a challenging area of research that is rapidly expanding in our daily life. To meet robot’s object detection requirements in a messy surrounding, this paper provides a visual object detection method based on color and shape features. Firstly, a color hierarchical model and a multi-size filter are built to obtain initial object regions from scene image. Then a straight line-corner-arc

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

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

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

In this research, we intend to present an enhanced object detection system incorporating a few well-known computer vision techniques, machine learning algorithms, as well as smart sensors in a more organized way. In essence, a computer vision based system in cooperation with machine learning approach has been employed to detect objects in parallel with a hardware-based ultrasonic sensor unit. The units

Based on the previous works in Lei and Lin (Syst Control Lett 56:529–537, 2007) and Kim et al. (Control Eng Pract 12:149–154, 2004) two kinds of novel universal output feedback controllers are proposed to solve the unmeasurable states problem for a uncertain missile system. Furthermore, in order to solve the unknown control direction problem which is not considered in the above reference, the unilateral

Coverage is a basic and critical issue for design and deployment of visual sensor networks, however, the optimization problem is very challenging especially when considering coverage of three-dimensional (3-D) scenarios. This paper provides a brief survey of mainstream coverage optimization methods for visual sensor networks, including the greedy algorithm, genetic algorithm (GA), particle swarm optimization

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

Flexible/soft manipulators have the potential to maneuver in confined space and reach deeply-seated targets via curvy trajectories, thus enjoy increasing popularity in minimally invasive surgery (MIS) community. We aim to automate palpation movement for this type of robots, an important procedure for disease diagnosis, where multiple force and pose requirements are to be achieved simultaneously. It’s

Functional electrical stimulation (FES) has recently been proposed as a supplementary torque assist in lower-limb powered exoskeletons for persons with paraplegia. In the combined system, also known as a hybrid neuroprosthesis, both FES-assist and the exoskeleton act to generate lower-limb torques to achieve standing and walking functions. Due to this actuator redundancy, we are motivated to optimally

In this paper, an impedance-controlled multi-master/single-slave telerobotic system is developed for haptics-enabled surgical training and cooperation in beating-heart surgery. This system not only can enable automatically motion compensation for the beating heart’s motion as well as non-oscillatory force feedback to the human operators but can also enable training and cooperation for multiple users

Mitigating ground effect becomes a big challenge for autonomous aerial vehicles when they are flying in close proximity to the ground. This paper aims to develop a precise model of ground effect on mini quadcopters, provide an advanced control algorithm to counter the model uncertainty and, as a result, improves the command tracking performance when the vehicle is in the ground effect region. The mathematical

There is a strong interest in the scope of human–industrial robot collaboration (HIRC) in manufacturing industry for greater flexibility and productivity. However, HIRC in manufacturing is still in its infancy; industrial practitioners have many apprehensions and uncertainties concerning the system’s performance and human operators’ safety. Therefore, there is a need for investigations into design

Active assistive systems for mobility aids are largely restricted to environments mapped a-priori, while passive assistance primarily provides collision mitigation and other hand-crafted behaviors in the platform’s immediate space. This paper presents a framework providing active short-term assistance, combining the freedom of location independence with the intelligence of active assistance. Demonstration

Autonomous underwater vehicles (AUVs) have become central to data collection for scientific and monitoring missions in the coastal and global oceans. To provide immediate navigational support for AUVs, computational data-driven flow models described as generic environmental models (GEMs) construct a map of the environment around AUVs. This paper proposes a data assimilation framework for the GEM to