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Mobile robots often follow humans in warehouse environments or indoor office spaces. A mobile robot requires a control system that stably follows humans without colliding with them. A human-following robot is composed of target detection, target tracking, and control. Conventional 2D laser-based human following systems exploit information from 2D planar laser data to detect human legs through machine learning methods, such as support vector data description and random forest. However, in crowded or cluttered environments, 2D LiDAR data is limited by the lack of features that distinguish human legs from obstacles. Due to the lack of features, false-positive detection is a problem in crowded or cluttered environments. Recent studies using 3D LiDAR have used sensors mounted at an elevated height to measure the overall shape of a person to extract features. Typical mobile robots are mounted in the bottom due to the vibration of the sensors, so there is a cost problem that additional sensors are required. We propose a framework for human following using 3D LiDAR. Our method is able to detect human legs using a LiDAR sensor attached at a low position without additional sensors. This study proposes a 3D laser-based human leg detection and tracking framework to improve the robustness of human-following for autonomous mobile robots. With a deep learning-based human leg detector, using the Point-Voxel-RCNN model, the proposed 3D human leg tracking system can help robots robustly follow humans in cluttered and crowded environments. Additionally, we demonstrate the robustness of our method in a practical cluttered environment by comparing the performance of a conventional human leg detection and following system. [ABSTRACT FROM AUTHOR]

The development of vision-based navigation systems for mobile robotics applications in outdoor scenarios is a very challenging problem due to frequent changes in contrast and illumination, image blur, pixel noise, lack of image texture, low image overlap and other effects that lead to ambiguity in the interpretation of motion from image data. To mitigate the problems arising from multiple possible interpretations of the data in outdoor stereo egomotion, we present a fully probabilistic method denoted as probabilistic stereo egomotion transform. Our method is capable of computing 6-degree of freedom motion parameters solely based on probabilistic correspondences without the need to track or commit key point matches between two consecutive frames. The use of probabilistic correspondence methods allows to maintain several match hypothesis for each point, which is an advantage when ambiguous matches occur (which is the rule in image feature correspondence problems), because no commitment is made before analysing all image information. Experimental validation is performed in simulated and real outdoor scenarios in the presence of image noise and image blur. Comparison with other current state-of-the-art visual motion estimation method is also provided. Our method is capable of significant reduction of estimation errors mainly in harsh conditions of noise and blur. [ABSTRACT FROM AUTHOR]

This article analyses and mathematically describes a method for mutual identification of multiple mobile robots. The method interchanges identification numbers among multiple robots via audible beeps multiplexed by frequency. The identification sound is sent only when robots approach to each other. The algorithm was primary designed for e-puck robots, but it can be used in any multi-agent robotic system; each mobile robot has to be equipped with three microphones for determination of the sound's direction, speaker and signal processing microcontroller. [ABSTRACT FROM AUTHOR]

In this article, we propose a novel discrete-time iterative learning control framework for robust path-tracking problem of nonholonomic mobile robots. The contributions of this iterative learning control framework are threefolds: (1) With the application of a conventional feedback-aided P-type learning algorithm, the tracking error caused by a nonzero initial shift is detected. (2) By the introduction of an initial rectifying term, a novel iterative learning control scheme is proposed to improve the tracking performance. Sufficient conditions of convergence of this approach are given. (3) The convergence of the proposed algorithm for achieving the desired trajectory over a specified interval is proven theoretically. Simulation results validate the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

Common control systems for mobile robots include the use of some deterministic control law coupled with some pose estimation method, such as the extended Kalman filter, by considering the certainty equivalence principle. Recent approaches consider the use of partially observable Markov decision process strategies together with Bayesian estimators. These methods are well suited to handle the uncertainty in pose estimation but demand significant processing power. In order to reduce the required processing power and still allow for multimodal or non-Gaussian uncertain distributions, we propose a scheme based on a particle filter and a corresponding cloud of control signals. The approach avoids the use of the certainty equivalence principle by postponing the decision on the optimal estimate to the control stage. As the mapping between the pose space and the control action space is nonlinear and the best estimation of robot pose is uncertain, postponing the decision to the control space makes it possible to select a better control action in the presence of multimodal and non-Gaussian uncertainty models. Simulation results are presented. [ABSTRACT FROM AUTHOR]

The article deals with integrating the inertial navigation unit implemented into the system of controlling the robot. It analyses the dynamic properties of the sensors of the inertial unit, for example, gyroscopes and accelerometers. The implementation of the original system of controlling the mobile robot on the basis of autonomous navigation systems is a dominant part of the article. The integration of navigational information represents the actual issue of reaching higher accuracy of required navigational parameters using more or less accurate navigation systems. The inertial navigation is the navigation based on uninterrupted evaluation of the position of a navigated object by utilizing the sensors that are sensitive to motion, that is, gyroscopes and accelerometers, which are regarded as primary inertial sensors or other sensors located on the navigated object. [ABSTRACT FROM AUTHOR]

This article proposes a control scheme for formation of maneuvers of a team of mobile robots. The control scheme integrates the integral sliding mode control method with the nonlinear disturbance observer technique. The leader- follower formation dynamics suffer from uncertainties originated from the individual robots. The uncertainties challenge the formation control of such robots. Assuming that the uncertainties are unknown but bounded, an nonlinear disturbance observer-based observer is utilized to approximate them. The observer outputs feed on an integral sliding mode control-based controller. The controller and observer are integrated into the control scheme to realize formation maneuvers despite uncertainties. The formation stability is analyzed by means of the Lyapunov's theorem. In the sense of Lyapunov, not only the convergence of the approximation errors is guaranteed but also such a control scheme can asymptotically stabilize the formation system. Compared to the results by the sole integral sliding mode control, some simulations are presented to demonstrate the feasibility and performance of the control scheme. [ABSTRACT FROM AUTHOR]

A whole resolved motion rate control algorithm designed for mobile dual-arm redundant robots is presented in this article. Based on this algorithm, the end-effector movements of the dual arms of the mobile dual-arm redundant robot can be decomposed into the movements of the two driving wheels of the differential driving platform and the movements of the dual-arm each joint of this robot harmoniously. The influence of the redundancies of the single- and dual-arm robots on the operation based on the fixed- and differential-driving platforms, which are then based on the whole resolved motion rate control algorithm, is studied after building their motion models. Some comparisons are made to show the advantages of this algorithm on the entire modeling of the complicated robotic system and the influences of the redundancy. First, the comparison of the simulation results between the fixed single-arm robot and the mobile single-arm robot is presented. Second, a comparison of the simulation results between the mobile single-arm robot and the mobile dual-arm robots is shown. Compared with the mobile single-arm robot and the fixed dual-arm robot based on this algorithm, the mobile dual-arm robot has more redundancy and can simultaneously track and operate different objects. Moreover, the mobile dual-arm redundant robot has better smoothness, more flexibility, larger operational space, and more harmonious cooperation between the two arms and the differential driving platform during the entire mobile operational process. [ABSTRACT FROM AUTHOR]

This article addresses the problem of trajectory tracking in crops by a weed sprayer mobile robot (WSMR). This problem arises because to fumigate, the robot must follow a predefined path and avoid any obstacles it may encounter. To achieve both trajectory tracking and obstacle avoidance, a control scheme based on different behaviours is proposed, which consists essentially of an adaptive controller with a reference model for trajectory tracking and a fuzzy reactive for obstacle avoidance. Each of these controllers is executed according to the selection of the fuzzy behaviour controller, which uses information delivered by anticollision sensors located on the robot. As a result of the implementation of this behaviour-based architecture and by means of computer simulations and experimental laboratory tests, the WSMR demonstrates the capability of autonomously following a desired trajectory between the rows of a crop in the presence of obstacles. The results are evaluated by taking into account trajectory tracking curves and the operating requirements of each controller, as well as the application of different errors indices for quantitatively evaluating the proposed control scheme. [ABSTRACT FROM AUTHOR]

This paper presents an iterative learning control (ILC) strategy to resolve the trajectory tracking problem of wheeled mobile robots (WMRs) based on dynamic model. In the previous study of WMRs' trajectory tracking, ILC was usually applied to the kinematical model of WMRs with the assumption that desired velocity can be tracked immediately. However, this assumption cannot be realized in the real world at all. The kinematic and dynamic models of WMRs are deduced in this chapter, and a novel combination of D-type ILC algorithm and dynamic model of WMR with random bounded disturbances are presented. To analyze the convergence of the algorithm, the method of contracting mapping, which shows that the designed controller can make the velocity tracking errors converge to zero completely when the iteration times tend to infinite, is adopted. Simulation results show the effectiveness of Dtype ILC in the trajectory tracking problem of WMRs, demonstrating the effectiveness and robustness of the algorithm in the condition of random bounded disturbance. A comparative study conducted between D-type ILC and compound cosine function neural network (NN) controller also demonstrates the effectiveness of the ILC strategy. [ABSTRACT FROM AUTHOR]

This paper introduces the pseudo-bacterial potential field (PBPF) as a new path planning method for autonomous mobile robot navigation. The PBPF allows us to obtain an optimal and safe path, in contrast to the classical potential field approach which is not suitable for path planning because it lacks a means of obtaining the optimal proportional gains. The PBPF uses the pseudo-bacterial genetic algorithm (PBGA) and a fitness function based on the potential field concepts to construct viable paths in dynamical environments to mostly result in the optimal path being obtained. Comparative experiments of sequential and parallel implementations of the PBPF for off-line and online in structured and unstructured conditions are presented; the results are contrasted with the artificial potential field (APF) method to demonstrate how the PBPF proposal overcomes the traditional method. [ABSTRACT FROM AUTHOR]

This article discusses the problem of usability of the USB 2.0 protocol in the area of real-time control of a mobile robot. Optimization methods of data transfer handling were proposed. The impact of the optimization results on the entire system's performance was examined in practice. As a test-bed, a hybrid system composed of two devices communicating by direct USB connection was implemented. The first of the mentioned devices was a 32-bit SoC micro-system serving as a direct control unit, and the second one was an off-the-shelf PDA providing supervisory control and logging. Due to this design, the system meets regimes of the real-time constraints and maintains continuity of a data stream at a large bandwidth. The real-time performances of subsystems and the entire system were experimentally examined depending on various operating conditions. Thanks to the performed experiments, the dependency of real-time limits on operational parameters has been determined. [ABSTRACT FROM AUTHOR]

This article discusses the problem of usability of the USB 2.0 protocol in the area of real-time control of a mobile robot. Optimization methods of data transfer handling were proposed. The impact of the optimization results on the entire system's performance was examined in practice. As a test-bed, a hybrid system composed of two devices communicating by direct USB connection was implemented. The first of the mentioned devices was a 32-bit SoC micro-system serving as a direct control unit, and the second one was an off-the-shelf PDA providing supervisory control and logging. Due to this design, the system meets regimes of the real-time constraints and maintains continuity of a data stream at a large bandwidth. The real-time performances of subsystems and the entire system were experimentally examined depending on various operating conditions. Thanks to the performed experiments, the dependency of real-time limits on operational parameters has been determined. [ABSTRACT FROM AUTHOR]

Intelligent mobile robotic agents demand optimal motion planners with minimal query time. Most contemporary algorithms lack one of these two required aspects. This paper proposes an efficient path-planning scheme based on cellular automata (CA) that generates optimal paths in the minimum time. A Cellular automaton is evolved over the entire search space and subsequently used for the determination of the shortest path. This approach generates a parent-child relationship for each cell in order to minimize the search time. Performance comparisons with A*, Dijkstra's, D* and MPCNN have proven it to be time-efficient. Analysis, simulation and experimental results have proven it to be a robust and complete path-planning scheme. Also it has demonstrated to be time-efficient in both static and dynamic environments. [ABSTRACT FROM AUTHOR]

Path planning is a fundamental optimization problem that is crucial for the navigation of a mobile robot. Among the vast array of optimization approaches, we focus in this paper on Ant Colony Optimization (ACO) and Genetic Algorithms (GA) for solving the global path planning problem in a static environment, considering their effectiveness in solving such a problem. Our objective is to design an efficient hybrid algorithm that takes profit of the advantages of both ACO and GA approaches for the sake of maximizing the chance to find the optimal path even under real-time constraints. In this paper, we present smartPATH, a new hybrid ACO-GA algorithm that relies on the combination of an improved ACO algorithm (IACO) for efficient and fast path selection, and a modified crossover operator to reduce the risk of falling into a local minimum. We demonstrate through extensive simulations that smartPATH outperforms classical ACO (CACO), GA algorithms. It also outperforms the Dijkstra exact method in solving the path planning problem for large graph environments. It improves the solution quality up to 57% in comparison with CACO and reduces the execution time up to 83% as compared to Dijkstra for large and dense graphs. In addition, the experimental results on a real robot shows that smartPATH finds the optimal path with a probability up to 80% with a small gap not exceeding 1m in 98%. [ABSTRACT FROM AUTHOR]

In this paper, we propose a computational trajectory generation algorithm for swarm mobile robots using local information in a dynamic environment. The algorithm plans a reference path based on constrained convex nonlinear optimization which avoids both static and dynamic obstacles. This algorithm is combined with one-step-ahead predictive control for a swarm of mobile robots to track the generated paths and reach the goals without collision. The numerical simulations and experimental results demonstrate the effectiveness of the proposed free-collision path planning algorithm. [ABSTRACT FROM AUTHOR]

This paper presents a motion control for an autonomous robot navigation using fuzzy logic motion control and stereo vision based path-planning module. This requires the capability to maneuver in a complex unknown environment. The mobile robot uses intuitive fuzzy rules and is expected to reach a specific target or follow a prespecified trajectory while moving among unforeseen obstacles. The robot's mission depends on the choice of the task. In this paper, behavioral-based control architecture is adopted, and each local navigational task is analyzed in terms of primitive behaviors. Our approach is systematic and original in the sense that some of the fuzzy rules are not triggered in face of critical situations for which the stereo vision camera can intervene to unblock the mobile robot. [ABSTRACT FROM AUTHOR]

This paper presents a motion control for an autonomous robot navigation using fuzzy logic motion control and stereo vision based path-planning module. This requires the capability to maneuver in a complex unknown environment. The mobile robot uses intuitive fuzzy rules and is expected to reach a specific target or follow a prespecified trajectory while moving among unforeseen obstacles. The robot's mission depends on the choice of the task. In this paper, behavioral-based control architecture is adopted, and each local navigational task is analyzed in terms of primitive behaviors. Our approach is systematic and original in the sense that some of the fuzzy rules are not triggered in face of critical situations for which the stereo vision camera can intervene to unblock the mobile robot. [ABSTRACT FROM AUTHOR]

This paper proposes a robust tracking controller based on a Generalized Extended State Observer (GESO) method for a wheeled mobile robot (WMR) with unknown skidding and slipping. Skidding and slipping of a WMR are inevitable in practice. We regard skidding and slipping as disturbances and modify the dynamics model to consider them simply. Then, we adopt the GESO to design a robust tracking controller at kinematic and dynamic level. Using Lyapunov theory, we derive the control law and guarantee the stability of the control system. The proposed control achieves attenuation of the disturbance and convergence of the tracking errors. The performance of the proposed method is verified by some simulation results. [ABSTRACT FROM AUTHOR]

The SCORPIO is a small-size mini-teleoperator mobile service robot for booby-trap disposal. It can be manually controlled by an operator through a portable briefcase remote control device using joystick, keyboard and buttons. In this paper, the speech interface is described. As an auxiliary function, the remote interface allows a human operator to concentrate sight and/or hands on other operation activities that are more important. The developed speech interface is based on HMM-based acoustic models trained using the SpeechDatE-SK database, a small-vocabulary language model based on fixed connected words, grammar, and the speech recognition setup adapted for low-resource devices. To improve the robustness of the speech interface in an outdoor environment, which is the working area of the SCORPIO service robot, a speech enhancement based on the spectral subtraction method, as well as a unique combination of an iterative approach and a modified LIMA framework, were researched, developed and tested on simulated and real outdoor recordings. [ABSTRACT FROM AUTHOR]

Mobile robot navigation has remained an open problem over the last two decades. Mobile robots are required to navigate in unknown and dynamic environments, and in recent years the use of mobile robots in material handling has considerably increased. Usually workers push carts around warehouses and manually handle orders which is not very cost-effective. To this end, a potential method to control a swarm of mobile robots in a warehouse with static and dynamic obstacles is to use the wireless control approach. Further, to be able to control different types of mobile robots in the warehouse, the fuzzy logic control approach has been chosen. Therefore, in this paper, an on-line navigation technique for a wheeled mobile robot (WMR) in an unknown dynamic environment using fuzzy logic techniques is investigated. In this paper, we aim to use the robot in application in a warehouse. Experimental results show the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

This paper represents a robust backstepping tracking control based on a Lyapunov redesign for Skid-Steered Wheeled Mobile Robots (WMRs). We present kinematic and dynamic models that explicitly relate the perturbations to the skidding in order to improve the tracking performance during real running. A robust controller is synthesized in the backstepping approach and the Lyapunov redesign technique, which forces the error dynamics to stabilize to the reference trajectories. We design an additional feedback control - a Lyapunov redesign - such that the overall control stabilizes the actual system in the presence of uncertainty and perturbation with the knowledge of the Lyapunov function. Simulation results are provided to validate and analyse the performance and stability of the proposed controller. [ABSTRACT FROM AUTHOR]

There is a growing interest in applying intelligent technologies to assistant robots. These robots should have a number of characteristics such as autonomy, easy reconfiguration, robust perception systems and they should be oriented towards close interaction with humans. In this paper we present an automatic hotel assistant system based on a series of mobile platforms that interact with guests and service personnel to help them in different tasks. These tasks include bringing small items to customers, showing them different points of interest in the hotel, accompanying the guests to their rooms and providing them with general information. Each robot can also autonomously handle some daily scheduled tasks. Apart from user-initiated and scheduled tasks, the robots can also perform tasks based on events triggered by the building's automation system (BAS). The robots and the BAS are connected to a central server via a local area network. The system was developed with the Robotics Integrated Development Environment (RIDE) and was tested intensively in different environments. [ABSTRACT FROM AUTHOR]

Ant Colony Optimization (ACO) is a population-based constructive meta-heuristic that exploits a form of past performance memory inspired by the foraging behaviour of real ants. The behaviour of the ACO algorithm is highly dependent on the values defined for its parameters. Adaptation and parameter control are recurring themes in the field of bio-inspired algorithms. The present paper explores a new approach to diversity control in ACO. The central idea is to avoid or slow down full convergence through the dynamic variation of certain parameters. The performance of different variants of the ACO algorithm was observed to choose one as the basis for the proposed approach. A convergence fuzzy logic controller with the objective of maintaining diversity at some level to avoid premature convergence was created. Encouraging results have been obtained on its application to the design of fuzzy controllers. In particular, the optimization of membership functions for a unicycle mobile robot trajectory control is presented with the proposed method. [ABSTRACT FROM AUTHOR]

Collective movement of mobile robots is the problem of how to control a group of robots making them move as a group, in a cohesive way, towards a common direction. Collective movement serves not only to move a group of robots from one point to another, but to perform more complex tasks such as using the group of robots as a moving sensor array, collective mapping and searching tasks. In this article, a survey of collective movement of mobile robots is done, including a classification and characterization of its different types, a review of the most important architectures and a list of its promising applications. [ABSTRACT FROM AUTHOR]

Aiming at the functional requirement of climbing up the stairs, the dynamics and stability during a tracked mobile robot's climbing of stairs is studied. First, from the analysis of its cross-country performance, the mechanical structure of the tracked mobile robot is designed and the hardware composition of its control system is given. Second, based on the analysis to its stairs-climbing process, the dynamical model of stairs-climbing is established by using the classical mechanics method. Next, the stability conditions for its stairs-climbing are determined and an evaluation method of its stairs-climbing stability is proposed, based on a mechanics analysis on the robot's backwards tumbling during the stairs-climbing process. Through simulation and experiments, the effectiveness of the dynamical model and the stability evaluation method of the tracked mobile robot in stairs-climbing is verified, which can provide design and analysis foundations for the tracked mobile robots' stairs-climbing. [ABSTRACT FROM AUTHOR]

In this paper, linear navigation law is studied in depth and we suggest an efficient, practical and simple approach for nonholonomic mobile robot navigation under velocity vector control based on the linear navigation law. First of all, an obstacle is equivalent to a velocity vector when detected by a robot's sensory system according to the relative distant and relative direction between the robot and the obstacle. Then the vector sum of all obstacles' equivalent velocity vectors (OEVVs) and the linear navigation velocity vector (LNVV) derived from the linear navigation law drives the robot to reach the desired goal position without colliding with any obstacle in the robot's workspace. Furthermore, during the process of driving the mobile robot under the resultant velocity vector, a set of strategies for velocity and acceleration constraints (VAC) is devised to make kinematic behaviours of the mobile robot more practical. Finally, to validate the effectiveness and superiority, extensive simulation results with no obstacles, a single obstacle and multiple obstacles are provided. [ABSTRACT FROM AUTHOR]

A combined kinematic/torque control law is developed by using a backstepping design approach for a nonholonomic mobile robot with two driving wheels mounted on the same axis to track a reference trajectory. The auxiliary velocity control inputs are designed for the kinematic steering system to make the posture error asymptotically stable. Next, a computed-torque controller is designed such that the mobile robot's velocities converge on the given velocity inputs in an optimal manner by converting the tracking control problem into the regulation problem whereby the uncertainties in the dynamics of mobile robots are considered. The proposed online and forward-in-time policy iteration (PI) algorithm based on approximate dynamic programming (ADP) is used to solve the optimal control problem with unknown internal dynamics by using single neural networks (NNs) to approximate the cost function. Afterwards, the near-optimal control policy can be computed directly according to the cost function, which removes the action network appearing in the ordinary ADP method. The stability of the dynamical extension system is demonstrated using Lyapunov methods. The simulation results are provided to demonstrate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

Previous research on mobile robots has been based on models of mobile robots with invariant weight parameters. However, the most practical mobile robots that bear heavy burdens have varying weights and centres of gravity. This paper suggests a design for an adaptive PD controller that estimates and adapts to the weight-related parameters of robots that bear varying heavy burdens. Using the suggested adaptive PD controller, the motion of mobile robots can be independent of the weight-related parameters and the operational performance is confirmed by target tracking simulations. [ABSTRACT FROM AUTHOR]

The autonomous vehicle is a mobile robot integrating multi-sensor navigation and positioning, intelligent decision making and control technology. This paper presents the control system architecture of the autonomous vehicle, called "Intelligent Pioneer", and the path tracking and stability of motion to effectively navigate in unknown environments is discussed. In this approach, a two degree-of-freedom dynamic model is developed to formulate the path-tracking problem in state space format. For controlling the instantaneous path error, traditional controllers have difficulty in guaranteeing performance and stability over a wide range of parameter changes and disturbances. Therefore, a newly developed adaptive-PID controller will be used. By using this approach the flexibility of the vehicle control system will be increased and achieving great advantages. Throughout, we provide examples and results from Intelligent Pioneer and the autonomous vehicle using this approach competed in the 2010 and 2011 Future Challenge of China. Intelligent Pioneer finished all of the competition programmes and won first position in 2010 and third position in 2011. [ABSTRACT FROM AUTHOR]

Multi-focal vision systems comprise cameras with various fields of view and measurement accuracies. This article presents a multi-focal approach to localization and mapping of mobile robots with active vision. An implementation of the novel concept is done considering a humanoid robot navigation scenario where the robot is visually guided through a structured environment with several landmarks. Various embodiments of multi-focal vision systems are investigated and the impact on navigation performance is evaluated in comparison to a conventional mono-focal stereo set-up. The comparative studies clearly show the benefits of multi-focal vision for mobile robot navigation: flexibility to assign the different available sensors optimally in each situation, enhancement of the visible field, higher localization accuracy, and, thus, better task performance, i.e. path following behavior of the mobile robot. It is shown that multi-focal vision may strongly improve navigation performance. [ABSTRACT FROM AUTHOR]

Obstacle avoidance is of great importance for path planning of manipulators in dynamic environment. To help manipulators successfully perform tasks, a method of path planning with obstacle avoidance is proposed in this article. It consists of two consecutive phases, namely, collision detection and obstacle-avoidance path planning. The collision detection is realized by establishing point-cloud model and testing intersection of axis-aligned bounding boxes trees, while obstacle-avoidance path planning is achieved through preplanning a global path and adjusting it in real time. This article has the following contributions. The point-cloud model is of high resolution while the speed of collision detection is improved, and collision points can be found exactly. The preplanned global path is optimized based on the improved D-star algorithm, which reduces inflection points and decreases collision probability. The real-time path adjusting strategy satisfies the requirement of reachability and obstacle avoidance for manipulators in dynamic environment. Simulations and experiments are carried out to evaluate the validity of the proposed method, and the method is available to manipulators of any degree of freedom in dynamic environment. [ABSTRACT FROM AUTHOR]

Boundary separation of operational regions would be helpful for unmanned surface vehicles deployed in dynamic outdoor environments. However, the feasibility and accuracy of current obstacle avoidance methods based on conventional optical images are comparatively poor for unmanned surface vehicle applications, with complicated natural illumination as one of the main sources of error. In this article, a new optical waterline detection method is proposed by combining shadow verification and global optimization (energy minimization). The method is then validated using an actual unmanned surface vehicle operating in outdoor environments. First, the basic principles of intrinsic image are introduced and then employed to evaluate the threshold for background segmentation so that the influence of complicated intensity distribution on the original image is reduced. The properties of different types of shadows are compared, and the basic principles of shadow verification are used to classify the different object regions. Subsequently, the intensity contrast between the shadow and non-shadow regions is used to measure the waterline position based on the relationship between the illumination and the shadow formation. Furthermore, the waterline detection problem is transformed into a problem involving the optimization of energy (minimization) described using differential equations. Finally, experiments are conducted with a series of practical images captured by the unmanned surface vehicle. The experimental results demonstrate the feasibility and robustness of the proposed method. [ABSTRACT FROM AUTHOR]

This article studies the inverse kinematics for asymmetric octahedral variable geometry truss manipulator with obstacle avoidance. The inverse kinematics problem is cast as a nonconvex optimization that having quadratic objective function subject to quadratic constraints. This article uses an inexact interior point optimization to solve it, which is developed on the basis of the imprecise algorithm Ipopt. According to the particularity of our actual optimization problem, each iteration undergoes specific modifications so as to minimize the memory consumption as well as computation time. Utilizing the sparse and binary characteristics of the coefficient matrix, respectively, the algorithm allocates the computation to the finite sparse matrix vector multiplication and changes the storage form, which greatly reduces the memory space. Based on the unique rules of inverse kinematics, the iteration direction of the algorithm becomes more clear. With the aid of mechanical constraints inherent in the manipulator, the algorithm omits the feasibility recovery part that embedded in the solver Ipopt. All these make us save the operation time greatly while utilizing Ipopt algorithm. To demonstrate the effectiveness of the proposed approach, the scheme was applied to obstacle avoidance inverse kinematics of variable geometry truss manipulator with three modules. [ABSTRACT FROM AUTHOR]

The main objective of this article is to present a controller capable of maintaining a chain formation of platooning type, among a set of non-holonomic mobile robots, keeping a time-gap separation between each pair of consecutive robots at the platoon. It is intended that the whole set of robots asymptotically follows any feasible trajectory described by the leader robot. Under these conditions, the distance between any pair of consecutive robots, that is, the i-th robot and the (i + 1)-th robot, depends on the velocity of the i-th robot. Only position measurements are available, such that, to avoid using approximate velocity estimations, the chain formation problem is solved by considering a delay observer strategy. Based on the measurements of the positions of the robots, along the platoon, a delay observer is built for the i-th robot that provides a virtual reference for the (i + 1)-th robot, and this reference corresponds to the i-th robot trajectory delayed specific units of time, corresponding to the desired time-gap separation. Convergence of the (i + 1)-th robot to its desired delayed trajectory, which implies convergence of the chain formation, is formally proved by means of a Lyapunov stability approach and supported by numerical simulations and real-time experiments. [ABSTRACT FROM AUTHOR]

This article is devoted to the design of robust position-tracking controllers for a perturbed wheeled mobile robot. We address the final objective of pose-regulation in a predefined time, which means that the robot position and orientation must reach desired final values simultaneously in a user-defined time. To do so, we propose the robust tracking of adequate trajectories for position coordinates, enforcing that the robot’s heading evolves tangent to the position trajectory and consequently the robot reaches a desired orientation. The robust tracking is achieved by a proportional–integral action or by a super-twisting sliding mode control. The main contribution of this article is a kinematic control approach for pose-regulation of wheeled mobile robots in which the orientation angle is not directly controlled in the closed-loop, which simplifies the structure of the control system with respect to existing approaches. An offline trajectory planning method based on parabolic and cubic curves is proposed and integrated with robust controllers to achieve good accuracy in the final values of position and orientation. The novelty in the trajectory planning is the generation of a set of candidate trajectories and the selection of one of them that favors the correction of the robot’s final orientation. Realistic simulations and experiments using a real robot show the good performance of the proposed scheme even in the presence of strong disturbances. [ABSTRACT FROM AUTHOR]

The article presents some aspects of a complex control system of a teleoperated military mobile robot Tactical Robotic System (TAROS) related to virtual reality and assistance to a human operator in general. Described is especially the unique and innovative system of virtual operator station which uses the HMD Oculus Rift to put the operator into a virtual space containing visual feedback from the robot and camera images, including stereovision. The virtual operator station serves as a cost-effective and portable replacement of what otherwise would be a large room with expensive equipment. Mentioned is also another system that helps the operator with remote manipulation tasks – the anti-collision system preventing damage done to the mechanical parts of the robot by incautious movements of the manipulator arm. [ABSTRACT FROM AUTHOR]

A haptic interface is a kinaesthetic link between a human and some real or virtual environment. In this article, we discuss whether the haptic technology (virtually touching objects and feeling forces) could be effectively implemented in the industrial applications. As an example, we will examine the virtual wall which is a fundamental component of almost all virtual objects. Typically, it is based on a simple spring and damper model with constraints that allow the user to make contact with an object. Various factors lead to an unstable behaviour in a controlled system such as the virtual wall. Main causes of disturbances are the sensor (e.g. the signal resolution) and the actuator (e.g. the dynamics of the system which are not covered by the controller design). Some of these disturbance mechanisms can be excluded by mechanical design, and others are more difficult to eliminate – following two are discussed in the article: First one is the zero-order hold effect caused by sampling and the second one is the shifted synchronization of the wall threshold crossings with the sampling times. Both have unwanted effects on the sampled data within the virtual wall system. [ABSTRACT FROM AUTHOR]