In this paper, a novel contour-tracking control method of an unknown planar object by lateral force regulation for wheeled mobile robot navigation is presented. The robot is required to follow the contour of an unknown object toward the goal position. Based on mobile robot dynamic equations, a force-control algorithm is proposed to maintain constant contact with a planar object. Measured contact force from an object is used not only to regulate a contact force in a lateral direction, but also to control the orientation angle of the robot to avoid collision with an object. Simulation and experiment of contour-tracking tasks of a wheeled mobile robot are conducted. Experimental results show that the contact force is well-regulated, and the robot arrives at the goal position successfully.

The work presented in this paper aims at providing a unified modelling framework for the reactive control of wheeled mobile manipulators (WMM). Where most work in the literature often provides models, sometimes simplified, of a given type of WMM, an extensive description of obtaining explicit kinematic and dynamic models of those systems is given. This modelling framework is particularly well suited for reactive control approaches, which, in the case of mobile manipulation missions, are often necessary to handle the complexity of the tasks to be fulfilled, the dynamic aspect of the extended workspace and the uncertainties on the knowledge of the environment. A flexible reactive framework is thus also provided, allowing the sequencing of operational tasks (in our case, tasks described in the end-effector frame) whose natures are different but also an on-line switching mechanism between constraints that are to be satisfied using the system redundancy. This framework has been successfully implemented in simulation and on a real robot. Some of the obtained results are presented.

Free-flying space manipulator systems, in which robotic manipulators are mounted on a free-flying spacecraft, are envisioned for assembling, maintenance, repair, and contingency operations in space. Nevertheless, even for fixed-base systems, control of mechanical manipulators is a challenging task. This is due to strong nonlinearities in the equations of motion, and consequently different algorithms have been suggested to control end-effector motion or force, since the early research in robotic systems. In this paper, first a brief review of basic concepts of various algorithms in controlling robotic manipulators is introduced. Then, specific problems related to application of such systems in space and a microgravity environment is highlighted. Basic issues of kinematics and dynamics modeling of such systems, trajectory planning and control strategies, cooperation of multiple arm space free-flying robots, and finally, experimental studies and technological aspects of such systems with their specific limitations are discussed.

This article synthezises the most important results on the kinematics of cuspidal manipulators i.e. nonredundant manipulators that can change posture without meeting a singularity. The characteristic surfaces, the uniqueness domains and the regions of feasible paths in the workspace are defined. Then, several sufficient geometric conditions for a manipulator to be noncuspidal are enumerated and a general necessary and sufficient condition for a manipulator to be cuspidal is provided. An explicit DH-parameter-based condition for an orthogonal manipulator to be cuspidal is derived. The full classification of 3R orthogonal manipulators is provided and all types of cuspidal and noncuspidal orthogonal manipulators are enumerated. Finally, some facts about cuspidal and noncuspidal 6R manipulators are reported.

The problem studied in this paper is a mobile robot that autonomously navigates in a domestic environment, builds a map as it moves along and localizes its position in it. In addition, the robot detects predefined objects, estimates their position in the environment and integrates this with the localization module to automatically put the objects in the generated map. Thus, we demonstrate one of the possible strategies for the integration of spatial and semantic knowledge in a service robot scenario where a simultaneous localization and mapping (SLAM) and object detection recognition system work in synergy to provide a richer representation of the environment than it would be possible with either of the methods alone. Most SLAM systems build maps that are only used for localizing the robot. Such maps are typically based on grids or different types of features such as point and lines. The novelty is the augmentation of this process with an object-recognition system that detects objects in the environment and puts them in the map generated by the SLAM system. The metric map is also split into topological entities corresponding to rooms. In this way, the user can command the robot to retrieve a certain object from a certain room. We present the results of map building and an extensive evaluation of the object detection algorithm performed in an indoor setting.

In this paper, we present a method for robot navigation toward a moving object with unknown maneuvers. Our strategy is based on the integration of the robot and the target kinematics equations with geometric rules. The tracking problem is modeled in polar coordinates using a two-dimensional system of differential equations. The control law is then derived based on this model. Our approach consists of a rendezvous course, which means that the robot reaches the moving goal without following its path. In the presence of obstacles, two navigation modes are integrated, namely the tracking and the obstacle-avoidance modes. To confirm our theoretical results, the navigation strategy is illustrated using an extensive simulation for different scenarios.

This paper addresses problems to achieve transparency and contact stability for teleoperation that consists of unconstrained and constrained motions. The adaptive bilateral control with a local force compensator is developed, based on adaptive impedance control and contact force driven compensation with auto-switching functions. Without any knowledge about robotic and environment dynamics and with a communication delay, the developed method guarantees good adaptive tracking performance in unconstrained motion and reduction of oscillating contacts in constrained motion. Based on an actual haptic device and a virtual manipulator, haptic simulations are presented to demonstrate adaptive transparency and contact stability in the presence of communication delay.

This paper presents the Genetic Algorithm Optimized Fourier Series Formulation (GAOFSF) method for stable gait generation in bipedal locomotion. It uses a Truncated Fourier Series (TFS) formulation with its coefficients determined and optimized by Genetic Algorithm. The GAOFSF method can generate human-like stable gaits for walking on flat terrains as well as on slopes in a uniform way. Through the adjustment of only a single or two parameters, the step length and stride-frequency can easily be adjusted online, and slopes of different gradients are accommodated. Dynamic simulations show the robustness of the GAOFSF, with stable gaits achieved even if the step length and stride frequency are adjusted by significant amounts. With its ease of adjustments to accommodate different gait requirements, the approach lends itself readily for control of walking on a rough terrain and in the presence of external perturbations.

There have been many interesting recent results in the area of geometrical methods for path planning in robotics. So it seems very timely to attempt a description of mathematical developments surrounding very elementary engineering tasks. Even with such limited scope, there is too much to cover in detail. Inevitably, our knowledge and personal preferences have a lot to do with what is emphasised, included, or left out.

Part I is introductory, elementary in tone, and important for understanding the need for geometrical methods in path planning. Part II describes the results on geometrical constructions that imitate well-known constructions from classical approximation theory. Part III reviews a class of methods where classical criteria are extended to curves in Riemannian manifolds, including several recent mathematical results that have not yet found their way into the literature.

In this paper, we consider the problem of rest-to-rest maneu-ver learning, via iterative learning control (ILC), for single-degree-of-freedom systems with stick-slip Coulomb friction and input bounds. The static coefficient of friction is allowed to be as large as three times the kinetic coefficient of friction. The input is restricted to be a two-pulse one. The desired input's first pulse magnitude is required to be five times the largest possible kinetic (sliding) friction force. The theory therefore allows the stiction force to be as large as the desired second input pulse. Under these conditions, we prove global convergence of a simple iterative learning controller. To the best of our knowledge, such a global-convergence proof has not been presented previously in the literature for the rest-to-rest problem with stick-slip Coulomb friction.

A characterization of singularities for a six-wire parallel architecture is presented as a result of numerical and experimental analyses. Numerical analysis has been developed through geometrical and analytical considerations. The study is based on a classification that has been derived on the basis of the geometry of tetrahedra, and singular configurations have been classified as a function of the tetrahedron volume. Experimental characterization has been carried out by considering the wire parallel architecture Cassino tracking system (CATRASYS). Experimental results are reported to characterize the performance of the CATRASYS chain in different operating conditions as an illustrative practical example.

The proposed algorithm integrates in a single planner the global motion planning and local obstacle avoidance capabilities. It efficiently guides the robot in a dynamic environment. This eliminates some of the traditional problems of planned architectures (model-plan-act scheme) while obtaining many of the qualities of behavior-based architectures. The computational efficiency of the method allows the planner to operate at high-rate sensor frequencies. This avoids the need for using both a collision-avoidance algorithm and a global motion planner for navigation in a cluttered environment. The method combines map-based and sensor-based planning operations to provide a smooth and reliable motion plan. Operating on a simple grid-based world model, the method uses a fast marching technique to determine a motion plan on a Voronoi extended transform extracted from the environment model. In addition to this real-time response ability, the method produces smooth and safe robot trajectories.

We propose a new, control theoretic methodology for defining performance measures of mobile manipulators. As a guiding principle, we assume that the kinematics or the dynamics of a mobile manipulator are represented by the end point map of a control system with outputs, and that a locally controllable system yields nontrivial performance measures. In the paper, we focus on two categories of dynamic performance measures: the compliance measure and the admittance measure. In both these categories, the following local and global performance characteristics are introduced: the agility ellipsoid, the agility and mobility, the condition number and the distortion. The usefulness of new local measures is demonstrated on the example of determining optimal motion patterns of a wheeled mobile robot.

A rotary positioner (RP) is a type of parallel manipulator that is similar to a Stewart Platform. Instead of having variable-length bars, however, an RP has constant-length limbs located between a mobile platform as well as six circular motors distributed on a circular base. This paper offers a detailed investigation of an RP, focusing on its mechanism and analyzing its forward and inverse kinematics. It also computes an RP's constant orientation and orientation workspaces, taking into account the constraints imposed by passive joints and links interference. The optimal combination of the main parameters for an RP's maximum possible translation and orientation is also provided.

Up to now, most people are still cooking in the kitchen, which makes them feel fatigued and also makes the air polluted. With the development of the numerical control technology, it becomes more and more urgent to apply the related technology to the automatic cooking field. In this paper, the cooking technique for the Chinese dishes is introduced and China's first cooking robot, named AI Cooking Robot (AIC), is presented. The robot mainly consists of four parts: the wok mechanism, the stirring-fry and dispersing mechanism, the feeding mechanism, and the mechanism of leaving the material in the middle process. In order to adjust the temperature, the fire control system is also given in this paper. Experiments show that the new robot will be a milestone in the cooking automation science because of its cooking technique.

A novel approach to estimate the real-time moving trajectory of an object is proposed in this paper. The object's position is obtained from the image data of a charge coupled device (CCD) camera, while a state estimator predicts the linear and angular velocities of the moving object. To overcome the uncertainties and noises residing in the input data, a Kalman filter and neural networks are utilized cooperatively. Since the Kalman filter needs to approximate a nonlinear system into a linear model in order to estimate the states, there still exist errors as well as uncertainties. To resolve this problem, in this approach, the Kohonen networks, which have a high adaptability to the memory of the input–output relationship, are utilized for the nonlinear region. In addition to this, the Kohonen network, as a sort of neural network, can effectively adapt to the dynamic variations and become robust against noises. This approach is derived from the observation that the Kohonen network is a type of a self-organized map and is spatially oriented, which makes it suitable for determining the trajectories of moving objects. The superiority of the proposed algorithm compared with the extended Kalman filter is demonstrated through real experiments.

The intention of this paper is to contribute towards a unified understanding of the basic notions and terms in the domain of humanoid robotics, having in mind that the same notions are sometimes interpreted in different ways (some interpretations are contradictory, and some even erroneous). Hence, the first part of the paper is devoted to defining some basic notions, walk and gait being among the first. Then, the paper deals with the notion of dynamic balance and stability, particularly the difference between them, since these essentially different notions are often confused and, rarely, regarded as identical. As dynamic balance is directly related to the notion of zero-moment point (ZMP), it was necessary to touch upon some misunderstandings concerning the ZMP. Gait stability is an especially delicate category, as humanoid locomotion systems have certain specific features that are not possessed by other systems. Namely, because of external disturbances, there may appear unpowered (passive) degrees of freedom that cause loss of dynamic balance. Hence, these unpowered degrees of freedom cannot be overlooked in the stability analysis. As the stability of motion of humanoid robots is inseparably linked with control, it was also necessary to pay due attention to this notion. Finally, the paper ends with a discussion of posture and postural stability with all their specificities. The authors hope that this paper will contribute to a clearer understanding of the basic notions of humanoid robotics, especially concerning robots with high dynamic and control performances.

This paper deals with sensor-based motion planning method for a robot arm manipulator operating among unknown obstacles of arbitrary shape. It can be applied to online collision avoidance with no prior knowledge of the obstacles. Infrared sensors are used to build a description of the robot's surroundings. This approach is based on the configuration space but the construction of the C-obstacle surface is avoided. The point automation is confined on some planes with square grids in the C-space. A path-searching algorithm based on square grids is used to guide the automation maneuvering around the C-obstacles on the selected planes. To avoid the construction of the C-obstacle surface, the robot geometry model is expanded, and the static collision detection method is used. Hence, the computation time is reduced and the algorithm can work in real time. The effectiveness of the proposed method is verified by a series of experiments.

This paper investigates the singular curves in the joint space of a family of planar parallel manipulators. It focuses on special points, referred to as cusp points, which may appear on these curves. Cusp points play an important role in the kinematic behavior of parallel manipulators since they make possible a nonsingular change of assembly mode. The purpose of this study is twofold. First, it exposes a method to compute joint space singular curves of 3-RPR planar parallel manipulators. Second, it presents an algorithm for detecting and computing all cusp points in the joint space of these same manipulators.

Due to its inherent advantages such as reasoning in the format of heuristic rules based on human experience and less stringent requirement on environmental description, fuzzy logic is a promising tool for the robot motion planning in 3-dimensional dynamic environment. In general, in the Cartesian space, the variables used in characterizing the motion of a mobile robot, such as position, velocity, and force relative to other objects or coordinate frames, contain both the magnitude and the pointing information. In previous studies, the fuzzy reasoning on the pointing information was often developed based on the decomposition of the pointing vector followed by conventional fuzzy logic technique on individual vector components. Consequently, when multiple pointing variables are involved, the number of fuzzy variables that need to be considered simultaneously becomes large and the rule base may become very complex, which diminishes the advantages of the fuzzy reasoning approach. In this research, we tackle this issue by implementing a new fuzzy reasoning approach based on vector-format fuzzy variables. To achieve this, a set of new membership functions is defined for the vector-format fuzzy variables, followed by the establishment of a series of new vector-based fuzzification, fuzzy inference, and defuzzification procedures. By treating the multidimensional variables as unitary linguistic variables, the number of fuzzy variables in the fuzzy propositions and therefore the scale of the rule base can be reduced considerably. As an application example, the proposed new fuzzy reasoning approach for motion planning is applied to an Underwater Robotics Vehicle (URV) operating in an oceanic environment, where the pointing of the goal and the pointing vectors of the obstacles are treated as vector-type fuzzy variables, which leads to a compact and significantly simplified rule base. The motion planner can successfully guide the URV to move in the complicated dynamic environ-ment in a real-time fashion, which clearly demonstrates the effectiveness and robustness of the new fuzzy logic approach.