Off-line Stage Research Articles

Development of a configuration space motion planner for robot in dynamic environment

In this paper, the on-line motion planning of articulated robots in dynamic environment is investigated. We propose a practical on-line robot motion planning approach that is based upon pre-computing the global configuration space (C-space) connectivity with respect to all possible obstacle positions. The proposed motion planner consists of an off-line stage and an on-line stage. In the off-line stage, the obstacles in the C-space (C-obstacle) with respect to the obstacle positions in the workspace are computed, which are then stored using a hierarchical data structure with non-uniform 2 m trees. In the on-line stage, the real obstacle cells in the workspace are identified and the corresponding 2 m trees from the pre-computed database are superposed to construct the real-time C-space. The collision-free path is then searched in this C-space by using the A* algorithm under a multi-resolution strategy which has excellent computational efficiency. In this approach, the most time-consuming operation is performed in the off-line stage, while the on-line computing only need to deal with the real-time obstacles occurring in the dynamic environment. The minimized on-line computational cost makes it feasible for real-time on-line motion planning. The validity and efficiency of this approach is demonstrated using manipulator prototypes with 5 and 7 degree-of-freedom.

Real-Time Volt/VAr Control Based on the Difference between the Measured and Forecasted Loads in Distribution Systems

This paper proposes a method for real-time control of both capacitors and ULTC in a distribution system to reduce the total power loss and to improve the voltage profile over the course of a day. The multi-stage consists of the off-line stage to determine dispatch schedule based on a load forecast and the on-line stage generates the time and control sequences at each sampling time. It is then determined whether one of the control actions in the control sequence is performed at the present sampling time. The proposed method is presented for a typical radial distribution system with a single ULTC and capacitors.

Reduced basis methods for Stokes equations in domains with non-affine parameter dependence

In this paper we deal with reduced basis techniques applied to Stokes equations. We consider domains with different shape, parametrized by affine and non-affine maps with respect to a reference domain. The proposed method is ideally suited for the repeated and rapid evaluations required in the context of parameter estimation, design, optimization, and real-time control. An “empirical”, stable and inexpensive interpolation procedure has permitted to replace non-affine coefficient functions with an expansion which leads to a computational decomposition between the off-line (parameter independent) stage for reduced basis generation and the on-line (parameter dependent) approximation stage based on Galerkin projection, used to find a new solution for a new set of parameters by a combination of previously computed stored solutions. As in the affine case this computational decomposition leads us to preserve reduced basis properties: rapid and accurate convergence and computational economies. The applications and results are based on parametrized geometries describing domains with curved walls, for example a stenosed channel and a bypass configuration. This method is well suited to treat also problems in fixed domain with non-affine parameters dependence expressing varying physical coefficients.

Robust MPC with Output Feedback and Realigned Model

In this work, it is presented a contribution to the design of the robust MPC with output feedback and input constraints. This work extends existing approaches by considering a particular non-minimal state space model, which transforms the output feedback strategy into a state feedback strategy. The controller is developed to the case in which the system inputs may become saturated. We follow a two stages approach. In the off-line stage, a series of unconstrained robust MPCs is obtained by including in the control optimization problem, inequality constraints that force the state of the closed-loop system to contract along the time. Each of these controllers is associated to particular sets of manipulated inputs and controlled outputs. In the existing version of the method, the closed loop system involves a state observer that makes the solution to the robust MPC optimization problem a time consuming step. In the on-line step of the controller design proposed procedure, a sub optimal control law is obtained by combining control configurations that correspond to particular subsets of available manipulated inputs. The method is illustrated with a simulation example of the process industry.

REAL-TIME VOLT/VAR CONTROL IN A DISTRIBUTION SYSTEM USING MULTI-STAGE METHOD

This paper proposes a method for real-time control of both capacitors and ULTC in a distribution system to reduce the total power loss and to improve the voltage profile over a day. Multi-stage consists of the off-line stage to determine dispatch schedule based on a load forecast and the on-line stage to generate the time and control sequences at each sampling time. It is then determined whether one of the control actions in the control sequence is performed at the present sampling time. The proposed method is presented for a typical radial distribution system with a single ULTC and capacitors.

Fuzzy process control: construction of control charts with fuzzy numbers

This paper presents the construction of fuzzy control charts for a process with fuzzy outcomes derived from the subjective quality ratings provided by a group of experts. The proposed fuzzy process control (FPC) methodology comprises an off-line stage and an on-line stage. In the off-line stage, experts assign quality ratings to products based on a numerical scale. The individual numerical ratings are then aggregated to form collective opinions expressed in the form of fuzzy numbers. The collective knowledge applied by the experts when conducting the quality rating process is acquired through a process of fuzzy regression analysis performed by a neural network. In the on-line stage, the product dimensions are measured, and the fuzzy regression model is employed to automate the experts’ judgments by mapping the measured dimensions to appropriate fuzzy quality ratings. The fuzzy quality ratings are then plotted on fuzzy control charts, whose construction and out-of-control conditions are developed using possibility theory. The developed control charts not only monitor the central tendency of the process, but also indicate its degree of fuzziness.

Selection of Strategies for Collision-free Motion in Multi-manipulator Systems

Strategy-based path planning was introduced by the authors as a way to give robotic manipulators some sort of reactive behaviour in dynamic and unpredictable environments. This approach is based on making robots react to moving obstacles using a restricted subset of the configuration space, and on using an off-line pre-planning stage to choose the restricted subset. In this paper, strategy-based path planning is applied and explored, focusing our attention on the off-line stage. It is applied to the joint motion of two and three robots that perform pick and place tasks sharing common working areas.

Reactive approach to on-line path planning for robot manipulators in dynamic environments

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.

Wavelet Analysis to Real-Time Fabric Defects Detection in Weaving processes

This paper introduces a vision-based on-line fabric inspection methodology of woven textile fabrics. Current procedure for determination of fabric defects in the textile industry is performed by human in the off-line stage. The advantage of the on-line inspection system is not only defect detection and identification, but also 벼ality improvement by a feedback control loop to adjust set-points. The proposed inspection system consists of hardware and software components. The hardware components consist of CCD array cameras, a frame grabber and appropriate illumination. The software routines capitalize upon vertical and horizontal scanning algorithms characteristic of a particular deflect. The signal to noise ratio (SNR) calculation based on the results of the wavelet transform is performed to measure any deflects. The defect declaration is carried out employing SNR and scanning methods. Test results from different types of defect and different style of fabric demonstrate the effectiveness of the proposed inspection system.

REACTIVE PATH PLANNING FOR ROBOTIC ARMS WITH MANY DEGREES OF FREEDOM IN DYNAMIC ENVIRONMENTS

It is well known that path planning for robots with many degrees of freedom is a complex task. That is the reason why the research on this area has been mostly restricted to static environments. This paper presents a new method for on-line path planning for robotic arms in dynamic environments. Most on-line path planning methods are based on local algorithms that end up being inefficient due to their lack of global information (local minima problems). The method presented in this paper avoids local minima by using a two stage framework. The robots react to dynamic environments using a local and reactive planning method restricted to a subset of its configuration space. Since the subset has few degrees of freedom the computational cost of the on-line stage is very low. An off-line stage chooses the subset of the configuration space that minimizes the probability of blockades and inefficient motions.

Multi-scale free-form 3D object recognition using 3D models

The recognition of free-form 3D objects using 3D models under different viewing conditions based on the geometric hashing algorithm and global verification is presented. The matching stage of the algorithm uses the hash-table prepared in the off-line stage. Given a scene of feature points, one tries to match the measurements taken at scene points to those memorised in the hash-table. The technique used for feature recovery is the generalisation of the CSS method (IEEE Trans. Pattern Anal. Mach. Intell., 14 (1992) 789–805), which is a powerful shape descriptor expected to be an MPEG-7 standard. Smoothing is used to remove noise and reduce the number of feature points to add to the efficiency and robustness of the system. The local maxima of Gaussian and mean curvatures are selected as feature points. Furthermore, the torsion maxima of the zero-crossing contours of Gaussian and mean curvatures are also selected as feature points. Recognition results are demonstrated for rotated and scaled as well as partially occluded objects. In order to verify match, 3D translation, rotation and scaling parameters are used for verification and results indicate that our technique is invariant to those transformations. Our technique for smoothing and feature extraction is more suitable than level set methods or volumetric diffusion for object recognition applications since it is applicable to incomplete surface data that arise during occlusion. It is also more efficient and allows for accurate estimation of curvature values.

Using geometric properties for automatic object positioning

This paper presents an application of some recent results in computer vision, in particular the use of geometric properties. The problem we examine here is the accurate positioning of an object with respect to another, say a tool. Such applications could be used in complex and hazardous environments like nuclear plants. Because high accuracy in positioning is our goal here, we suppose that the objects have planar faces on which targets can be put. Without loss of generality, we have used only two objects in our experiments. Throughout this paper, we have called them the reference object and the unknown object respectively. The positions of the targets of the reference object with their associated projective invariants are computed in an off-line stage. Hence, given at least two images of the two objects, we can automatically identify the reference object points in the images and reconstruct the points of the unknown object relative to the reference object. The experiments show that a precision of 0.1 mm in relative positioning can be reached for an object observed at a distance of 2 m.

On-line/off-line digital signatures

A new type of signature scheme is proposed. It consists of two phases. The first phase is performed off-line, before the message to be signed is even known. The second phase is performed on-line, once the message to be signed is known, and is supposed to be very fast. A method for constructing such on-line/off-line signature schemes is presented. The method uses one-time signature schemes, which are very fast, for the on-line signing. An ordinary signature scheme is used for the off-line stage. In a practical implementation of our scheme, we use a variant of Rabin's signature scheme (based on factoring) and DES. In the on-line phase all we use is a moderate amount of DES computation and a single modular multiplication. We stress that the costly modular exponentiation operation is performed off-line. This implementation is ideally suited for electronic wallets or smart cards.

Alternatives to fractional experimentation: an assessment and critique

In this article we evaluate alternative techniques to fractional experimentation and analysis, in particular those recommended by Dorian Shainin. His methods for variable identification and variation reduction at the on-line and off-line stage of a production process are described and assessed, viewed in relation to other methods for off-line quality control and on-line improvement.

Robot Manipulator Dynamics — Towards Better Computational Algorithms

A new robot manipulator inverse dynamics computational algorithm is announced. The novel feature resides in the computations which are a blend of ordinary and Boolean algebra. As such, this method may also be interpreted as a dedicated compiler that optimizes the on-line computing time at expenses of the off-line stage. Nevertheless, the high off-line requirements are alleviated, through the derivation of some general rules that stem from the structure of the robot manipulator equations. In a practical implementation, a computer program based on a Quine-McCluskey truth table simplification method was used and experimented on a 2R robot manipulator. The results show a considerable computational improvement on a conventional sequential machine. Furthermore, they clearly point out new computational parallel architectures, without scheduling problems, and where performance improvement is proportional to the number of processors. Finally, it is observed that the proposed algorithm is not restricted to robot inverse dynamic computations, but is also applicable to kinematic and control computations.

A real-time system for robot manipulator inverse dynamics computation

A new robot manipulator inverse dynamics computational algorithm is announced. The novel feature resides in the computations which are a blend of ordinary and Boolean algebra. As such, this method may also be interpreted as a dedicated compiler that optimizes the on-line computing time at expenses of the off-line stage. Nevertheless, the high off-line requirements are alleviated, through the derivation of some general rules that stem from the structure of the robot manipulator equations. Moreover, the on-line computing time is further optimized through the use of Binary Decision Diagrams. The results show a considerable computational improvement on a conventional sequential machine. Furthermore, they clearly point out new computational parallel architectures, without scheduling problems, and where performance improvement is proportional to the number of processors. Finally, it is observed that the proposed algorithm is not restricted to robot inverse dynamic computations, but is also applicable to many other real-time computing structures.

Sleep telemetry in the rat. II. Automatic identification and recording of vigilance states

An identification system for the vigilance states of the rat is described which uses as inputs the cortical EEG, neck muscle EMG and motor activity, and which allows concomitant monitoring of feeding and drinking behaviour. State identification and data recording are performed in an on-line and an off-line stage which are designed to accommodate a large number of data for computer processing.