In order to widen the potentialities of manipulation of the Laboratoire de Mécanique des solides (LMS) mechanical hand, we developed a new planning approach based on the use of a specific exoskeleton. This one has kinematics architecture and dimensions identical to the mechanical hand. This feature allows us to obtain manipulation trajectories for the mechanical hand, very easily and very quickly, by using the exoskeleton, without complex calibration. Manipulation's trajectories are replayed offline with an autonomous control, and, consequently, the exoskeleton is not used with any feedback strategy for telemanipulation. This paper presents the characteristics of this exoskeleton and the graphic interface that we developed. This one uses a method to determine the object's evolution during the manipulation with the exoskeleton, without using exteroceptive sensors. This new approach was tested for standard trajectories by simulation on a Computer-aided design (CAD) robotics system and by using the mechanical hand. Thus, we validate the use concept of an isomorphic exoskeleton to mechanical hand for manipulation planning with the LMS mechanical hand.

This paper is to investigate inherent oscillations problems of Potential Field Methods (PFMs) for nonholonomic robots in dynamic environments. In prior work, we proposed a modification of Newton's method to eliminate oscillations for omnidirectional robots in static environment. In this paper, we develop control laws for nonholonomic robots in dynamic environment using modifications of Newton's method. We have validated this technique in a multirobot search-and-forage task. We found that the use of the modifications of Newton's method, which applies anywhere C2 continuous navigation functions are defined, can greatly reduce oscillations and speed up robot's movement, when compared to the standard gradient approaches.

This paper presents simulation results for basic operation of CALUMA (CAssino Low-cost hUMAnoid robot). The new humanoid robot CALUMA is described with its characteristics of low-cost design and easy-operation behavior. A CALUMA model in ADAMS environment has been elaborated. The CALUMA ADAMS model has been used for a dynamic simulation of robot operation. Three modes for the dynamic simulation have been studied, namely straight walking, walking with a grasped object in the hand, and lifting an object. The results of simulating those basic operations show the feasibility of the proposed design for CALUMA robot and validate its operation. Improvements have been illustrated in the design evolution for the robot structure and operation as suggested by simulation results.

The paper is concerned with the relationship between the equation of elastic line motion, the “Euler-Bernoulli approach” (EBA), and equation of motion at the point of elastic line tip, the “Lumped-mass approach” (LMA). The Euler–Bernoulli equations (which have for a long time been used in the literature) should be expanded according to the requirements of the motion complexity of elastic robotic systems. The Euler–Bernoulli equation (based on the known laws of dynamics) should be supplemented with all the forces that are participating in the formation of the bending moment of the considered mode. This yields the difference in the structure of Euler–Bernoulli equations for each mode. The stiffness matrix is a full matrix. Mathematical model of the actuators also comprises coupling between elasticity forces. Particular integral of Daniel Bernoulli should be supplemented with the stationary character of elastic deformation of any point of the considered mode, caused by the present forces. General form of the elastic line is a direct outcome of the system motion dynamics, and can not be described by one scalar equation but by three equations for position and three equations for orientation of every point on that elastic line. Simulation results are shown for a selected robotic example involving the simultaneous presence of elasticity of the joint and of the link (two modes), as well the environment force dynamics.

We describe how Lie-theoretical methods can be used to analyze color related problems in machine vision. The basic observation is that the nonnegative nature of spectral color signals restricts these functions to be members of a limited, conical section of the larger Hilbert space of square-integrable functions. From this observation, we conclude that the space of color signals can be equipped with a coordinate system consisting of a half-axis and a unit ball with the Lorentz groups as natural transformation group. We introduce the theory of the Lorentz group SU(1, 1) as a natural tool for analyzing color image processing problems and derive some descriptions and algorithms that are useful in the investigation of dynamical color changes. We illustrate the usage of these results by describing how to compress, interpolate, extrapolate, and compensate image sequences generated by dynamical color changes.

Developing 6-DOF isotropic manipulators using isotropic generators is simple and efficient, and isotropic generators can be employed to develop serial, redundant, or parallel isotropic manipulators. An isotropic generator consists of a reference point and six straight lines. The existing generators, however, have one common geometric constraint: the reference point is equidistant from the six straight lines. Some practical isotropic designs might not be obtained due to this constraint. This paper proposes methods for developing new isotropic generators. The generators thus developed are not subject to the constraint, and the new methods allow us to specify the location of the tool center point, the size of the platform or the base, or the shape of isotropic parallel manipulators. Many new generators are presented to develop 6-DOF parallel manipulators with different shapes or different types of kinematic chains.

A general new methodology using evolutionary algorithms viz., Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) and Multi-objective Differential Evolution (MODE), for obtaining optimal trajectory planning of an industrial robot manipulator (PUMA 560 robot) in the presence of fixed and moving obstacles with payload constraint is presented. The problem has a multi-criterion character in which six objective functions, 32 constraints and 288 variables are considered. A cubic NURBS curve is used to define the trajectory. The average fuzzy membership function method is used to select the best optimal solution from Pareto optimal fronts. Two multi-objective performance measures namely solution spread measure and ratio of non-dominated individuals are used to evaluate the strength of Pareto optimal fronts. Two more multi-objective performance measures namely optimiser overhead and algorithm effort are used to find computational effort of the NSGA-II and MODE algorithms. The Pareto optimal fronts and results obtained from various techniques are compared and analysed. Both NSGA-II and MODE are best for this problem.

Recent advances in simultaneous localization and mapping permit robots to autonomously explore enclosed environments and, subsequently, navigate to selected positions within them. But, for many tasks, it is more useful to immediately navigate to goals in unexplored environments, without a map. This is possible if a human director can describe the ideal route to the robot using grounded symbols that both parties can perceive directly.

In this paper, a mobile robot is autonomously navigated to many locations in a cluttered laboratory environment by a variety of routes. A series of topological navigation instructions are provided in advance by the director, in a form that can be expressed verbally and translates easily to software representation. The instructions are based on the perception of spatial affordances available to the robot, namely nearby junctions and edges in a pruned Generalized Voronoi Diagram. The operator can generate the instructions by viewing or imagining the environment without any measurements. Only three to five instructions are needed to navigate anywhere in our laboratory. The instructions contain only topology. No spatial measurements or environmental data such as landmarks are provided to the robot.

This paper presents analysis and experimental verifications of a new robot manipulator with five degrees of freedom developed for the buffing operation of shoes. First, the forward and inverse kinematics are analyzed. Next, an analytic closed-form solution is rigorously derived for the joint angles corresponding to the position and orientation of the end-effector in Cartesian coordinates. A control system, including input/output interfaces and the related electronic system, is designed for the control of the mechanical structure of the buffing robot. Then, peripheral systems integrated with the conveyer, transfer device, and fixture device are designed for the sequential buffing process of shoes. Also, a graphic user interface (GUI) program including the forward/inverse kinematics, control algorithm, and communication program to interact the robot with the peripheral systems is developed by using visual C++ language. A new flexible toolholder (FTH) is proposed to compensate for the excessive applied force between deburring tools and shoes. Finally, the test results are provided to demonstrate the effectiveness of the proposed scheme.

This paper presents a two-level control strategy for bipedal walking mechanism that accounts for implicit control of push-off on the between-step control level and tracking of imposed holonomic constraints on kinematic variables via feedback control on within-step control level. The proposed control strategy was tested in a biologically inspired model with minimal set of segments that allows evolution of human-like push-off and power absorption. We investigated controller's stability characteristics by using Poincaré return map analysis in eight simulation cases and further evaluated the performance of the biped walking model in terms of how variations in torso position and gait velocity relate to push-off and power absorption. The results show that the proposed control strategy, with the same set of controller's gains, enables stable walking in a variety of chosen gait parameters and can accommodate to various trunk inclinations and gait velocities in a similar way as seen in humans.

Knowledge of the physical properties of terrain surrounding a planetary exploration rover can be used to allow a rover system to fully exploit its mobility capabilities. Terrain classification methods provide semantic descriptions of the physical nature of a given terrain region. These descriptions can be associated with nominal numerical physical parameters, and/or nominal traversability estimates, to improve mobility prediction accuracy. Here we study the performance of multisensor classification methods in the context of Mars surface exploration. The performance of two classification algorithms for color, texture, and range features are presented based on maximum likelihood estimation and support vector machines. In addition, a classification method based on vibration features derived from rover wheel–terrain interaction is briefly described. Two techniques for merging the results of these “low-level” classifiers are presented that rely on Bayesian fusion and meta-classifier fusion. The performance of these algorithms is studied using images from NASA's Mars Exploration Rover mission and through experiments on a four-wheeled test-bed rover operating in Mars-analog terrain. Also a novel approach to terrain sensing based on fused tactile and visual features is presented. It is shown that accurate terrain classification can be achieved via classifier fusion from visual and tactile features.

A good practice to ensure high-positioning accuracy in industrial robots is to use joint error maximum mutual compensation (JEMMC). This paper presents an application of JEMMC for positioning of hexapod robots to improve end-effector positioning accuracy. We developed an algorithm and simulation framework in MatLab to find optimal hexapod configurations with JEMMC. Based on a real hexapod model, simulation results of the proposed approach are presented. Optimal hexapod configurations were found using the local minimum of the infinity norm of hexapod Jacobian inverse. JEMMC usage in hexapod robots can improve hexapod end-effector positioning accuracy by two times and more.

A system including Global Positioning Systems (GPS) and digital cartography is a good solution to carry out vehicle's guidance. However, it has inconveniences like high sensibility to multipath and interference when the GPS signal is blocked by external agents. Another system is mandatory to avoid this error. This paper presents a cooperative system based on GPS and Inertial Navigation Systems (INS) for automated vehicle position. The control system includes a decision unit to choose which value is the correct. In case GPS is working at top precision, it takes the control. On the other part, GPS signal can be lost and inertial control system guides the car in this occasion. A third possibility is contemplated: we receive the signal from GPS but the accuracy is over one meter. Now, position value is obtained by means of both systems. Experimental results analyze two situations: guidance in an urban area where GPS signal can be occluded by buildings or trees during short time intervals and the possibility of loss of the signal in long time to simulate the circulation in tunnels. Good results have been observed in tests and it demonstrates how a cooperative system improves the automated vehicle guidance.

An algorithm for three-level hierarchical sensor fusions has beenproposed and applied to environment map building with enhanced accuracy and efficiency. The algorithm was realized through the two new types of sensor modules, which are composed of a halogen lamp-based active vision sensor and a semicircular ultrasonic (US) and infrared (IR) sensor system. In the first-level fusion, the US and IR sensor information is utilized in terms of the geometric characteristics of the sensor location. In the second-level fusion, the outputs from the US and IR sensors are combined with the sheet of halogen light through a proposed rule base. In the third-level fusion, local maps from the first- and second-level fusion are updated in a probabilistic way for a very accurate environment local map. A practical implementation has been carried out to demonstrate the efficiency and accuracy of the proposed hierarchical sensor fusion algorithm in environment map building.

The state-of-the-art FastSLAM algorithm has been shown to cause a particle depletion problem while performing simultaneous localization and mapping for mobile robots. As a result, it always produces over-confident estimates of uncertainty as time progresses. This particle depletion problem is mainly due to the resampling process in FastSLAM, which tends to eliminate particles with low weights. Therefore, the number of particles to conduct loop-closure decreases, which makes the performance of FastSLAM degenerate. The resampling process has not been thoroughly analyzed even though it is the main reason for the particle depletion problem. In this paper, standard resampling algorithms (systematic residual and partial resampling), a rank-based resampling adopting genetic algorithms are analyzed using computer simulations. Several performance measures such as the effective sample size, the number of distinct particles, estimation errors, and complexity are used for the thorough analysis of the resampling algorithms. Moreover, a new compensation technique is proposed instead of resampling to resolve the particle depletion problem in FastSLAM. In estimation errors, the compensation technique outperformed other resampling algorithms though its run-time was longer than those of others. The most appropriate time to instigate compensation to reduce the run-time was also analyzed with the diminishing number of particles.

The research, described in this paper, concerns the robot indoor navigation, emphasizing the aspects of sensor model and calibration, environment representation, and self-localization. The main point is that combining all of these aspects, an effective navigation system is obtained. We present a model of the catadioptric image formation process. Our model simplifies the operations needed in the catadioptric image process. Once we know the model of the catadioptric sensor, we have to calibrate it with respect to the other sensors of the robot, in order to be able to fuse their information. When the sensors are mounted on a robot arm, we can use the hand-eye calibration algorithm to calibrate them. In our case the sensors are mounted on a mobile robot that moves over a flat floor, thus the sensors have less degrees of freedom. For this reason we develop a calibration algorithm for sensors mounted on a mobile robot. Finally, combining all the previous results and a scan matching algorithm that we develop, we build 3D maps of the environment. These maps are used for the self-localization of the robot and to carry out path following tasks. In this work we present experiments which show the effectiveness of the proposed algorithms.

Polyhedral scene analysis studies whether a 2D line drawing of a 3D polyhedron is realizable in space, and if so, it gives the results of parameterizing the space of all possible realizations. For generic 2D data, symbolic computation with Grassmann–Cayley algebra is needed in the analysis. In this paper, we propose a method called parametric calotte propagation to solve the realization and parameterization problems for general polyhedral scenes at the same time. In algebraic manipulation, parametric propagation is more efficient than elimination. In applications, it can lead to linear construction sequences for nonspherical polyhedra whose resolvable sequences do not exist.

In this paper, dead-reckoning localization errors for automated guided vehicles (AGVs) in indoors quasi-structured environments are studied. Based on error ellipse localization analysis, dead-reckoning errors arising from mismatched AGV wheels radius are investigated. The dynamic model for a differential-drive AGV type with mismatched wheels radius is also derived. The developed rationale shows that sensor fusion is a key feature for minimizing AGV localization errors. Two simulation scenarios and one experiment are presented to show system performance under AGV proportional-derivative (PD)-type control.

A two-channel bilateral controller is proposed for teleoperation systems. The controller takes into account both the free space motion and the constrained motion. Specifically, the force-position (F-P) architecture is applied during the constrained motion, while the position-position (P-P) architecture is applied during the free space motion. Theoretically, perfect transparency can be achieved. In addition, it does not need to switch the control modes of the master and the slave controllers during the transition between the free space motion and the constrained motion. Experiments are conducted to validate the analysis, and to demonstrate the effectiveness of the proposed bilateral controller. The limitations of the proposed controller are also discussed.

This investigation describes the mechanical configuration and control environment for a novel cart-seesaw system. This mechanism is called a super articulated mechanical system (SAMS). The system comprises a cart that slides on the pneumatic rodless cylinder. The rodless cylinder is double-acting with the carrier bracket, on which a cart is a pinion mechanism for the tracks. The cart-seesaw system brings the cart from any initial position to a desired position on the seesaw by applying an appropriate force to the cart and thus adjusting the angle of the seesaw. The position of a cart denotes the first degree of freedom, which is activated by a pneumatic proportional valve, and the angle of the seesaw indicates the second degree of freedom that is not actuated. Consequently, the proposed new pneumatic cart-seesaw system is straightforward to construct and direct to operate in different scenarios of performance. A state feedback controller is applied for stabilization of the equilibrium point of the system. Moreover, this study adds a supervisory controller that takes control action in extreme situations. Test results reveal excellent properties in control performance. The proposed product can be extensively applied in SAMS and pneumatic control for robotics control laboratory.