The Motion Tomography (MT) algorithm maps an ocean flow field using sporadically measured positions of underwater vehicles. A key step of the MT algorithm, called trajectory tracing, is to estimate the underwater trajectories of the vehicles based on the estimated flow field and known start and end positions. This paper extends the MT algorithm by developing a set of analytical formulas to compute

For the benefits of productivity, efficiency and sustainability, the adoption of machine vision with robotics in applications has become essential in agriculture industry; for example, outdoor tender-tealeaf harvesting, where tasks are highly repetitive and laborious. As machine vision must cope with changing daylight conditions, among the challenges is an efficient technique to accurately detect/locate

Sit-to-stand (STS) movement is a very common task for the elderly and the patients with lower limb dysfunction in daily life. We hope to summarize the methods of STS experiment and the factors affecting STS, and provide a reference for future STS experimental researches. We selected the relevant STS experimental studies, analyzed and compared the methods and results of these studies, and the suggestions

In this paper, we present a novel model-free fractional-order adaptive back-stepping control scheme for the wearable exoskeletons with constraints on the joint angle tracking errors. Firstly, the ultra-local model based intelligent proportion integration differentiation (iPID) control is combined with time delay estimation (TDE) to realize a model-free feature, and the precise modeling process can

Abstract Heavy oil thermal cracking is a complex multivariable and important petrochemical reaction process. The accurate kinetic models are of great significance for the simulation and analysis of this process. In this paper, a membrane computing optimization algorithm with multi-subsystems (MCOA) is proposed to solve parameter estimation problems of the heavy oil thermal cracking model. In MCOA,

Industrial robots can perform delicate operations, and they have good stability and durability. However, robots adapt with difficulty to changes in tasks and environments, and they basically can only perform operations in a fixed logic sequence. In contrast, humans can adapt to changes in the environment at any time due to their strong hand–eye coordination. Humans can quickly adjust their limbs to

Multirotor airplanes are widely used in many outdoor applications, e.g., agriculture, transportation, and public safety, where winds might be strong and prevalent. However, the effects of wind on multirotor aircraft are still not fully understood yet. The objective of this paper is to investigate and model wind effects on a real hovering octocopter. The wind is directly measured and considered as one

Detection accuracy and speed are crucial in object detection in computer vision. This work proposes a novel technique called On-Category Anchors (OC-Anchors) to improve the accuracy of real-time single-stage object detectors. The key concept of the OC-Anchors technique is to create anchors based on the categories of foreground objects. The OC-Anchors are set to reflect the bounding box features of

This paper presents a non-singular terminal sliding mode control (NTSMC) design based on an improved extended state observer (IESO) with application to an omnidirectional mobile manipulator (OMM) for trajectory tracking control. Firstly, a unified dynamic model is derived based on Lagrange method for an OMM prototype. An IESO that can reduce the initial peaking phenomenon is applied to estimate the

In this paper, a decentralized motion planning approach for multi-quadrotor autonomous navigation is developed in environments populated with obstacles. We propose a priority-based RRT algorithm, which generates an online global path for each quadrotor with obstacle avoidance. Furthermore, the front-end paths uncross by assigning priorities and sharing global states in the swarm. The security and clearance

To perform object grasping in dense clutter, we propose a novel algorithm for grasp detection. To obtain grasp candidates, we developed instance segmentation and view-based experience transfer as part of the algorithm. Subsequently, we established an algorithm for collision avoidance and stability analysis to determine the optimal grasp for robot grasping. The strategy for the view-based experience

Owing to advantages of large workspace and flexible movement, wheeled mobile robots are widely applied in industry. With vision module for environment perception, visual servoing of wheeled mobile robots has been one of the hottest research topics in robotic fields. Due to different demands for various applications and specific properties of the system, many challenges are faced for designing visual

Perception of the environment is the prerequisite for the realization of unmanned driving. Correctly detecting the lane line and navigating the vehicle is the key technology in unmanned driving. This paper mainly aims at the low accuracy of the traditional lane detection algorithm in the complex environment such as night and rain, and proposes a lane detection and recognition method based on dynamic

This paper presents a summary of mechanisms for the evolution of artificial intelligence in ‘internet of things’ networks. Firstly, the paper investigates how the use of new technologies in industrial systems improves organisational resilience supporting both a technical and human level. Secondly, the paper reports empirical results that correlate academic literature with Industry 4.0 interdependencies

The measurement accuracy of wind direction and wind speed is very important to the unmanned sailboat control, but the mature mechanical wind sensor and ultrasonic wind sensor both have great defects to be applied to the unmanned sailboat. Inspired by previous works on neural networks, we propose a low-cost, real-time, and robust wind measurement system based on computer vision (CV). This CV-wind-sensor

The lidar-inertial-based simultaneous localization and mapping (SLAM) have been widely investigated in recent years. In this paper, a loosely-coupled lidar-inertial odometry and mapping method is developed for robot state estimation in real-time. The proposed lidar-inertial odometry is a loosely-coupled and nonlinear optimization-based method, fusing IMU measurements and pose of lidar odometry. Lidar

Robotic abrasive belt grinding can be widely used to improve the surface quality of complex workpieces. Due to the elastic characteristics in the grinding process, feasible processing parameters cannot be fully predicted by existing cutting models given a desired cutting depth. Thus, abrasive belt grinding in industrial production still relies mainly on operator experience and intelligence. Robust

Cooperative navigation (CN) is a widespread technique to have efficient navigation of intelligent vehicles. Nonetheless, the CN strategies need to be more consistent in estimating and managing in-road risks. This paper outlines a flexible CN scheme for multiple unmanned ground vehicles (MUGVs) system to deal with such critical cooperative system. With its relative low execution time, the probability

The biomechanical energy harvester is expected to harvest the electric energies from human motions. A tradeoff between harvesting energy and keeping the user’s natural movements should be balanced via optimization techniques. In previous studies, the hardware itself has been specialized in advance for a single task like walking with constant speed on a flat. A key ingredient is Continuous Variable

Soldiers working in the field of explosive ordnance disposal (EOD) wear cumbersome personal protective equipment (PPE) that may affect their performance in the field, limit their mobility, and cause discomfort. The objective of this study was to develop a test methodology to identify the relationship between EOD suit interface loads and mission-critical performance metrics. The physical interactions

This paper mainly focuses on the volume calculation of materials in the warehouse where sand and gravel materials are stored and monitored whether materials are lacking in real-time. Specifically, we proposed the sandpile model and the point cloud projection obtained from the LiDAR sensors to calculate the material volume. We use distributed edge computing modules to build a centralized system and

The bean leaves can be affected by several diseases, such as angular leaf spots and bean rust, which can cause big damage to bean crops and decrease their productivity. Thus, treating these diseases in their early stages can improve the quality and quantity of the product. Recently, several robotic frameworks based on image processing and artificial intelligence have been used to treat these diseases

In intelligent warehouse logistics, image classification is widely used. However, the performance of traditional image classifiers suffers when deployed in new environments because of the lack of labels collected. In this paper, aiming at solving the problem above, a novel method named non-negative discriminative collective target nearest-neighbour representation (NDCTNNR) is proposed. Inspired by

Recent works in the person re-identification task mainly focus on the model accuracy while ignoring factors related to efficiency, e.g., model size and latency, which are critical for practical application. In this paper, we propose a novel Hierarchical and Efficient Network (HENet) that learns hierarchical global, partial, and recovery features ensemble under the supervision of multiple loss combinations

The obstacles avoidance of manipulator is a hot issue in the field of robot control. Artificial Potential Field Method (APFM) is a widely used obstacles avoidance path planning method, which has prominent advantages. However, APFM also has some shortcomings, which include the inefficiency of avoiding obstacles close to target or dynamic obstacles. In view of the shortcomings of APFM, Reinforcement

This paper introduces a new indoor way-finding method for the visually impaired person (VIP) by utilizing the naturally-generated inertial and geomagnetic information. Reliable and accurate indoor orientation and localization are provided by newly designed sensor fusion algorithms, which take advantage of inertial and geomagnetic information and overcome the inherent problems of the naturally-generated

In this paper, an accurate, large range, two-axis compliant positioning system is described and the performance of the implemented control system is analysed. The characteristics of two independently controlled axes are designed to be nominally identical and orthogonal. Both the kinematic and the kinetostatic cross-coupling interactions between the axes are statically analysed. The movement of each

In this paper, a new multi-robot task allocation (MRTA) algorithm inspired by the Newtonian law of gravity is proposed. In the proposed method, targets and robots are considered as fixed objects and movable objects, respectively. For each target, a constant mass is assigned, which corresponds to its quality. The fixed objects (which refer to targets) apply a gravitational force to the movable objects

This paper focuses on the optimal tracking control problem for robot systems with environment interaction and actuator saturation. A control scheme combined with admittance adaptation and adaptive dynamic programming (ADP) is developed. The unknown environment is modelled as a linear system and admittance controller is derived to achieve compliant behaviour of the robot. In the ADP framework, the cost

This study addresses a novel discrete finite-time fault compensation method for a quadruped robot leg when the parameter uncertainties and the actuator faults affect the robot dynamics. The occurrence times, shapes, and pattern of the faults are completely unknown. The actuator faults and dynamic uncertainties are reconstructed precisely in finite-time based on discrete-time super twisting estimator

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