The paper focuses on the problem of point-to-point trajectory planning for flexible redundant robot manipulators (FRM) in joint space. Compared with irredundant flexible manipulators, a FRM possesses additional possibilities during point-to-point trajectory planning due to its kinematics redundancy. A trajectory planning method to minimize vibration and/or executing time of a point-to-point motion is presented for FRMs based on Genetic Algorithms (GAs). Kinematics redundancy is integrated into the presented method as planning variables. Quadrinomial and quintic polynomial are used to describe the segments that connect the initial, intermediate, and final points in joint space. The trajectory planning of FRM is formulated as a problem of optimization with constraints. A planar FRM with three flexible links is used in simulation. Case studies show that the method is applicable.

This paper describes a new approach to path planning of robot manipulators with many degrees of freedom. It is designed for on-line motion in dynamic and unpredictable environments. The robots react to moving obstacles using a local and reactive algorithm restricted to a subset of its configuration space. The lack of a long-term view of local algorithms (local minima problems) is solved using an off-line pre-planning stage that chooses the subset of the configuration space that minimises the probability of not finding collision free paths. The approach is implemented and tested on a system of three Scorbot-er IX five link robots.

A software tool for data mining (DMiner-I) is introduced, which integrates pattern recognition (PCA, Fisher, clustering, HyperEnvelop, regression), artificial intelligence (knowledge representation, decision trees), statistical learning (rough set, support vector machine), and computational intelligence (neural network, genetic algorithm, fuzzy systems). It consists of nine function models: pattern recognition, decision trees, association rule, fuzzy rule, neural network, genetic algorithm, HyperEnvelop, support vector machine and visualization. The principle, algorithms and knowledge representation of some function models of data mining are described. Nonmonotony in data mining is dealt with by concept hierarchy and layered mining. The software tool of data mining is realized by Visual C++ under Windows 2000. The software tool of data mining has been satisfactorily applied in the prediction of regularities of the formation of ternary intermetallic compounds in alloy systems, and diagnosis of brain glioma.

A method for searching the best location of a path in the robot workspace considering the velocity performance of the robot is presented. After a thorough investigation of the robot performance indices, a new measure for the velocity efficiency of a robot moving its end-effector along a path is introduced. This measure is an approximation of the minimum of the Manipulator Velocity Ratio (MVR) along the path. The minimum is calculated from a finite set of MVRs determined at specified points of the path using an algorithm for an approximate motion of the end effector along the path.

The introduced measure is used as the objective function in an optimisation problem, where an optimal location of the path is searched. The objective function is procedural and non continuous, so a Genetic Algorithm is used to search the space for the optimal location of the path. The proposed method is tested using a simulated PUMA-like robot, which has to move its end-effector along a straight-line segment. At the end of the paper, the results obtained in these tests are presented and discussed.

In this paper, we investigate trajectory tracking in a multi-input nonlinear system, where there is little knowledge of the system parameters and the form of the nonlinear function. An identification-based iterative learning control (ILC) scheme to repetitively estimate the linearity in a neighborhood of a desired trajectory is presented. Based on this estimation, the original nonlinear system can track the desired trajectory perfectly by the aid of a regional training scheme. Just like in adaptive control, a singularity exists in ILC when the input coupling matrix is estimated. Singularity avoidance is discussed. A new parameter modification procedure for ILC is presented such that the determinant of the estimate of the input coupling matrix is uniformly bounded from below. Compared with the scheme used for adaptive control of a MIMO system, the proposed scheme reduces the computation load greatly. It is used in a robotic visual system for manipulator trajectory tracking without any information about the camera-robot relationship. The estimated image Jacobian is updated repetitively and then its inverse is used to calculate the manipulator velocity without any singularity.

In this paper we describe a heuristic potential based technique for solving the problem of path planning based on local information for a free flying robot (FFR) in a 3D static environment. A path which maximizes the sum of three functions: (repulsion from obstacles, attraction towards the goal, and level attraction) is chosen. While the repulsive and goal-attraction potentials depend on how close is the FFR from obstacles and goal, respectively, the level-attraction potential maintains a certain altitude at which the FFR should navigate. Two additional heuristics are proposed to overcome the local minima problem and to improve the efficiency of the search process. Simulation results of the proposed technique are presented.

This paper discusses a technique for identifying the joint parameters of a modular robot in order to study the dynamic characteristics of the whole structure and to realise dynamic control. A method for identifying the joint parameters of the structure applying fuzzy logic combined with a genetic algorithm has been studied using a 9-DOF modular redundant robot. A Genetic Algorithm was used in the fuzzy optimisation, which helped to avoid converging to locally optimal solutions and made the results identified much more reasonable. The joint parameters of a 9-DOF modular redundant robot have been identified.

This paper presents an adaptation of Lowe's numerical model-based camera localisation algorithm to the domain of indoor mobile robotics. While the original method is straightforward and even elegant, it nonetheless exhibits certain weaknesses. First, due to an affine approximation, the method is not consistent with perspective projection especially when the dimensions of objects seen are large in comparison with their distances to the camera. Next, the non-linearity of equations makes convergence properties sensitive both to the initial solution estimate and to noise. By taking the specificity and exigency of the mobile robotics domain into account, a new formulation of this method is proposed in order to improve efficiency, accuracy and robustness in the presence of noisy data and variable initial conditions. According to this formulation, line correspondences are used rather than points, the number of degrees of freedom is reduced, the affine approximation is removed and rotation is uncoupled from translation. Test results with both synthetic and real images illustrate the improvements expected from theoretical modifications.

This paper presents an attractive position-based visual servoing approach for camera-in-hand robotic systerns. The major contribution of this work is in devising an elegant and pragmatic approach for 3D visual tracking, which yielded good target tracking performance. It differs from the other known techniques, in its approach for image interpretation and the introduction of a Smith-like predictor control structure to overcome the inherent multi-rate time delayed nature of the visual servoing system. A complete description is made of the proposed MSP-DH visual servoing system. Experiments on the target tracking performance on XY planar motion using an AdeptOne robotic system are presented to illustrate the controller performance. In addition, experimental results have clearly shown the capability of the MSP-DH visual servoing system in performing 3D-dynamic visual servoing.

This paper addresses the problem of finding a nonholonomic path subject to a curvature restriction, to be tracked by a wheeled autonomous navigation vehicle. This robot is able to navigate in a structured environment, with obstacles modeled as polygons, thus constituting a model based system. The path planning methodology begins with the conditioning of the polygonal environment by offsetting each polygon in order to avoid the possibility of collision with the mobile. Next, the modified polygonal environment is used to compute a preliminary shortest path (PA) between the two extreme positions of the trajectory in the plane (x, y). This preliminary path (PA) does not yet consider the restrictions on the curvature and is formed only by straight line segments. A smoothing process follows in order to obtain a path (PS) that satisfies curvature restrictions which consist basically of joining the straight line segments by circular arcs of minimum radius R (filleting). Finally, the initial and final orientation of the vehicle are accounted for. This is done using a technique we have called the Star Algorithm, because of the geometric shape of the resulting maneuvers. A final complete path (PC) is thus obtained.

This paper deals with the path planning of non-holonomic vehicles on an uneven natural terrain. It uses the properties of incompressible viscous fluid fields. The full configuration is considered including position and orientation. Lanes are computed instead of a single path. Bounds on curvature and constraints on initial and final orientations are also addressed. By using the Keymeulen/Decuyper fluid method and adding friction forces in the Stokes' equations, the shortest paths or the minimum energy ones can be found, even on an uneven terrain. In addition, in order to satisfy the kinematics and dynamics constraints of a non-holonomic robot a local variation of the shear constraint is used to control the upper bound of the trajectory curvature. Adding small corridors at the departure and destination also satisfies initial and final orientation requirements.

This paper presents a general methodology for the off-line planning of optimal trajectory of robot manipulators by taking into account the grasping forces in the manipulator gripper. The mechanical energy of the actuators has been considered for the formulation of the objective function. The optimization problem has been formulated as subject to physical constraints, input torque/force constraints and payload constraints. The mathematical model takes into account the coupled nonlinear equations of manipulator motion. A numerical example shows the efficiency of the proposed procedure.

In this paper, two algorithms for solving the Inverse Dynamic Problem based on the Gibbs-Appell equations are proposed and verified. Both are developed using mainly vectorial variables, and the equations are expressed in a recursive form. The first algorithm has a computational complexity of O(n2) and is the least efficient of the two; the second algorithm has a computational complexity of O(n). This algorithm will be compared with one based on Newton-Euler equations of motion, formulated in a similar way, and using mainly vectors in its recursive formulation. The O(n) proposed algorithm will be used to solve the Inverse Dynamic Problem in a PUMA industrial robot.

Planar parallel manipulators, with potential applications in high speed, high acceleration tasks such as electronic component placement, would be subject to mechanical vibration due to high inertial forces acting on the linkages and other components. To achieve high throughput capability, such motion induced vibration would have to be damped quickly, to reduce settling time of the platform position and orientation. This paper develops a two-time scale dynamic model of a three-degree-of-freedom planar parallel manipulator with structurally flexible linkages. Based on the two-time scale model, a composite controller, consisting of a computed torque controller for the slow time-scale or rigid body subsystem dynamics, and a linear-quadratic state-feedback regulator for the fast time-scale flexible dynamic subsystem, is designed. Simulation results show that the composite control scheme permits the parallel manipulator platform to follow a given desired trajectory, while damping structural vibration arising due to excitation from inertial forces.

CaPaMan (Cassino Parallel Manipulator) is a 3-Degree Of Freedom spatial parallel manipulator that has been designed at the Laboratory of Robotics and Mechatronics, in Cassino. In this paper we present a formulation for an optimum design for CaPaMan architecture when the orientation workspace is suitably specified.

The manipulator with a large degree of redundancy is useful for realizing multiple tasks such as maneuvering the robotic arms in the constrained workspace, e.g. the task of maneuvering the end-effector of the manipulator along a pre-specified path into a window. This paper presents an on-line technique based on a posture generation rule to compute a null-space joint velocity vector in a singularity-robust redundancy resolution method. This rule suggests that the end of each link has to track an implicit trajectory that is indirectly resulted from the constraint imposed on tracking motion of the end-effector. A proper posture can be determined by sequentially optimizing an objective function integrating multiple criteria of the orientation of each link from the end-effector toward the base link as the secondary task for redundancy resolution, by assuming one end of the link is clamped. The criteria flexibly incorporate obstacle avoidance, joint limits, preference of posture in tracking, and connection of posture to realize a compromise between the primary and secondary tasks. Furthermore, computational demanding of the posture is reduced due to the sequential link-by-link computation feature. Simulations show the effectiveness and flexibility of the proposed method in generating proper postures for the collision avoidance and the joint limits as a singularity-robust null-space projection vector in maneuvering redundant robots within constrained workspaces.

This paper proposes a new orientation representation of planar manipulators by resorting to polar coordinates. Connecting the end-effector point to the first joint of a manipulator with a virtual adjustable link, the length of the adjustable link corresponds to a workspace point and is related to the orientation of the end effector link by a virtual angle in the form of a transcendental equation. Plotting this link length against the virtual angle in polar coordinates, the orientation of a manipulator can be represented in a compact form, and the range of partial dexterity can be identified. The characteristics of the new representation is hence revealed and related to the assessment of an orientation capability of a manipulator. Based on this representation, a desirable task can be presented and a manipulator can be synthesised with the required orientation.

This paper focuses on using a singularly perturbed approach to derive a vibration damping control law in which a pole assignment feedback method is utilized. The composite control system is characterized by two components which can be computed separately. The one is Cartesian-based PI control which drives the end-effector of a flexible manipulator to track the desired time-based trajectory. The other is pole assignment feedback control which damps out vibrations during and at the end of trajectory tracking. An advantage of this composite control method in real implementation is that it does not require a derivative of the end-effector's position, and the derivatives of signals from the strain gauges. From the characteristics and implementation points of view, it appears to be simple to use. Laboratory experiments were conducted to evaluate the performance of the proposed control method.

In this paper, the robust adaptive control and observer are considered for a pneumatic robot leg. This approach does not require a precise knowledge of the robot model physical parameters, only the adaptive upper bounds on the norm of the matrices model are used, which with the sliding mode guarantee the robustness of system. Convergence conditions and simulation results for the adaptive control and observer are presented.

This paper proposes a method for transversal passing through singularities of corank 1, both for nonredundant and redundant robotic manipulators. The method modifies the Jacobian matrix of manipulator's forward kinematics to retrieve its full rank at singularities. Natural candidates for the Jacobian matrix modification are derivatives of determinants of full size sub-matrices of the Jacobian matrix. The method is illustrated with examples, including a PUMA manipulator and 2-link and 3-link planar manipulators. Some restrictions on the applicability of the method for nonredundant manipulators are also discussed.