Mobile robotics is a very attractive research field. There are two main reasons for this. The first is the high number of applications and sectors where these machines could be introduced in the future: transport, agriculture, military, aerospace, etc. The second reason is that mobile robots are excellent test-beds to develop and integrate the results of many other research areas: control, computer vision, electronics, mechanics, artificial intelligence, etc. The third IFAC Symposium on Intelligent Autonomous Vehicles was an opportunity to present some of the latest developments in the area. Authors presented not only new methods and technologies to solve the classical problems related to intelligent autonomous vehicles, which include path planning, localization, environment modeling, path following, etc., but also new approaches to their design, such as new architectures, new navigation procedures, self-learning systems, etc. In addition, many different applications and vehicles were considered: from autonomous ocean vehicles to planetary rovers. This special issue of Robotica comprises some revised and updated selected papers of the Symposium. The variety of selected papers includes surveys, applications and design and development aspects of intelligent autonomous vehicles.

This paper considers a dynamic and adaptive trajectory generator for negotiating paths using S-curves. Applying constant jerk transitions between the constant acceleration and deceleration periods of the trajectory, the trajectory will optimally transition to the desired speed setting. Optimal is defined to be the minimum time to transition from the current speed to the set speed for the move segment when jerk and acceleration are limited. The S-curve equations will adapt to instantaneous changes in speed setting and path length. An integrated motion planner will determine allowable speeds and transitional profiles based on the remaining move distance.

At the end of the 20th century robot technology became well established as a reliable and economic source in industrial automation. On the other hand, it is claimed that even a general six or seven degree of freedom robot arm or a multifingered robot hand designed carefully and manufactured with very high precision lacks versatility in its use in a variety of tasks that must be done instead of a human. The lack of versatility or the clumsiness of present industrial robots is not due to the fine mechanism of such robots. Rather, the clumsiness shows a lack of our knowledge of everyday physics, in particular, a lack of knowledge of physics involving grasping and handling of various kinds of things and manipulating them with certain dexterity, in which tactile and vision sensings must be well coordinated.

ADVANCES IN AUTOMATION

1.Miniature machines

Cambridge UK scientists are attempting to cut groves in silicon chips just wide enough to contain one molecule of DNA. If successful it would mean that a hand-held device using such chips could be programmed to read the entire sequence of human DNA. Such computers could, for example, be built to identify causes of any sudden infectious diseases with a diagnosis obtained in minutes rather than in the days it could take using present-day technology. The report of these researches suggests that the whole process could then be a more controlled one with the readings taken being more precise. A comparison with current channel cutting methods was also given. Apparently, channels in a chip are normally cut to a measure of millionths of a metre, whilst the Cambridge researchers are now down to 100 millionth of a metre and confidently hope to achieve 10 billionths of a metre.

A new approach to the control of indirect simultaneous positioning of deformable objects is presented. Many manufacturing processes that deal with deformable objects such as clothes and rubber sheets involve a positioning of multiple points on a deformable object. The multiple points should be guided simultaneously to the desired locations. Moreover, these positioned points cannot be manipulated directly. This operation is referred to as indirect simultaneous positioning. In this article, we will propose a new control law for indirect simultaneous positioning of a deformable object based on its uncertain model and will show the robustness of the proposed control law. First, a simplified physical model of a deformable object is developed for its positioning operation. Second, indirect simultaneous positioning of an extensible object is formulated. Based on a linearized model of an extensible object, we will propose a novel control law for indirect simultaneous positioning. Next, we will prove the robustness of the proposed control law theoretically. Finally, experimental results will show the robustness of our proposed control law against the discrepancy between a real fabric and its uncertain model.

In this paper, an AEKF algorithm is used to localize a mobile robot equipped with eight Polaroid sonars in an indoor structured environment. The system state equation and sonar measurement models used for locating the mobile robot are set up. The localization process based on the AEKF algorithm is given. Four criteria used to judge the validity of predictive measurements of sonars are presented, which can increase the probability of the matching between predictive measurements and actual measurements. Experiments show that the localization precision based on our methods is greater than that using the conventional EKF algorithm.

This paper addresses the kinematic modelling, solutions and trajectory planning of a tele-laparoscopic manipulator. This type of manipulator can be used in remote positioning of laparoscopic tools through tele-operating system. Specifically the paper models kinematics of a typical manipulating system which can be used in such tele-surgery. Inverse kinematics solutions are also obtained for two kinematically constraint motions which are part of a typical trajectory of the laparoscopic tools. These are fixed axis rotation of the tool and its straight line motion. Simulation results are presented to demonstrate the validity of such models and solutions.

In this paper, two novel approaches to unmanned underwater vehicle path planning are presented. The main idea of the first approach, referred to as Constrained Optimisation (CO) is to represent the free space of the workspace as a set of inequality constraints using vehicle configuration variables. The second approach converts robot path planning into a Semi-infinite Constrained Optimisation (SCO) problem. The function interpolation technique is adopted to satisfy the start and goal configuration requirements. Mathematical foundations for Constructive Solid Geometry (CSG), Boolean operations and approximation techniques are also presented to reduce the number of constraints, and to avoid local minima. The advantages of these approaches are that the mature techniques developed in optimisation theory which guarantee convergence, efficiency and numerical robustness can be directly applied to the robot path planning problem. Simulation results have been presented.

This paper deals with the kinematic calibration of the Argos mechanism which is a novel, spherical parallel structure having 3 rotational degrees of freedom. Its design is based on 3 actuators carrying a pantograph each which are connected to the end-effector by means of 3 spherical joints. Two different calibration models are introduced. The first one models mechanical deviations in all parts except for the spherical joints and the assumption that they are moving on a perfect circle (“model 27”). The second model considers only deviations which affects the orientation of the end-effector but not its position assuming that the mechanism remains spherical (“model 9”). A measurement set-up allows to measure the full pose (position and orientation) of the end-effector with respect to its base. These measurement data are used to identify the parameters of the two calibration models resulting in an accuracy improvement of RMS (root mean squares errors) of a factor of 5.3 for the orientation and a factor of 3.4 for the prediction of the position.

This survey paper is focused on the navigation of mobile robots. The most important associated problems and the solutions given by different researchers are discussed. Several aspects are not yet satisfactorily resolved and some promising research approaches are addressed.

In this paper a multirobot system consisting of small size ball-shaped mobile underwater robots is introduced. Robots form a cooperative society operating together for a common goal. This is made possible by inter-member communication and control architecture allowing cooperation. The test environment is a closed aquatic process containing tanks, pipes, and a jet pump. The task considered is cleaning of biologically contaminated spots in the process. Detailed hardware structure of a robot-member as well as the control architecture are introduced. Behaviour of the cooperative system is demonstrated in a test environment where contamination caused by biological algae growth is emulated by infrared panels behaving like a living biomass.

We present an efficient obstacle avoidance control algorithm for redundant manipulators using a new measure called collidability measure. Considering moving directions of manipulator links, the collidability measure is defined as the sum of inverse of predicted collision distances between links and obstacles: This measure is suitable for obstacle avoidance since directions of moving links are as important as distances to obstacles. For kinematic or dynamic redundancy resolution, null space control is utilized to avoid obstacles by minimizing the collidability measure: We present a velocity-bounded kinematic control law which allows reasonably large gains to improve the system performance. Also, by clarifying decomposition in the joint acceleration level, we present a simple dynamic control law with bounded joint torques which guarantees tracking of a given end-effector trajectory and improves a kinematic cost function such as collidability measure. Simulation results are presented to illustrate the effectiveness of the proposed algorithm.

NASA has developed a free-flying camera known as AERCam to assist Space Shuttle and Space Station operations. The first AERCam vehicle was controlled from within the Space Shuttle using a hand-held controller. We have developed a system for controlling AERCam remotely from the ground, which involves significant communication delays. We have tested its use with NASA's AERCam dynamics simulation in place of the actual vehicle. Our ground system uses a predictive display1 that is based on a similar simulation of Shuttle and AERCam dynamics. For both physical and numeric reasons, the behavior of the remote vehicle may drift from what is expected by the predictive display system. We have developed a mechanism to periodically re-establish correspondence of the ground simulation with the remote vehicle using tracking data that reports AERCam's recent behavior. Our system also provides a basis for future development of more advanced autonomous ground control for space vehicles such as AERCam.

A 6-DOF motion bed is proposed as a nonlinear robust observer to solve the forward kinematics problem of a Stewart platform. The stability of the estimation error dynamics is proved via Lyapunov stability analysis and the error dynamics shows practical stability. An observer design algorithm which tackles the nonlinearity and uncertainty both in the system and in the output is presented by a new arithmetic Riccati equation. The estimation performance for the algorithm is verified using both simulations and experiments. The equation employs the bounding condition computed from the platform dynamics.

A new type of a parallel wire-driven robot is proposed in order to reach ultra-high speed. The driving principle of parallel wire systems is described. Since wires can only pull and not push on an object, at least n+1 wires are needed in order to move the object in a n-dimensional space. In this paper, taking account of the effect of such redundancy on actuation, the motion stability in wire length coordinates is analyzed by using a Lyapunov function. Using “Vector Closure”, it is proven that the hand position and orientation converge to the corresponding desired values and the internal force also converges to the desired one. Moreover, by making good use of non-linear elasticity of parallel wire driven robots, it is claimed that the internal force arising from redundant actuation can effectively reduce vibration when the high-speed robot stops at desired points. As a result, ultra-high speed with more than 40 g(g:gravitational acceleration) can be attained by using relatively small actuators.

For outdoor mobile robots localisation, GPS has obvious advantages: position data are directly given in an absolute frame, and the required infrastructure is reduced to a sole fixed station in the case of differential systems. Yet, the use of this solution raises a number of issues, such as the satellite maskings, or the existence of the so-called GPS latency which delays the output of the localisation data. This paper deals with the latter problem, and proposes a method to identify this parameter without using other exteroceptive sensors. Experimental results are presented based on trials carried out at the Centre d'Expérimentations Routières (CER) in Rouen, in collaboration with the Laboratoire Central des Ponts et Chaussées (LCPC).

In this paper, the use of algebraic and trigonometric splines for the trajectory planning of robot manipulators is discussed. First, the two methods are analyzed and compared in detail; then, a strategy, which involves a combined use of the two schemes to perform sudden changes in a predefined trajectory (e.g. in case of obstacle avoidance) is proposed. Results show that the main interest in using trigonometric splines lies especially in the task of connecting two separate pieces of cubic splines, as overshoots are significantly reduced, although the continuity of velocity, acceleration and (in case) jerk is guaranteed.

We present a general framework for modeling a class of mechanical systems for robotic manipulation, consisting of articulated limbs with redundant tendinous actuation and unilateral constraints. Such systems, that include biomorphically designed devices, are regarded as a collection of rigid bodies, inter-acting through connections that model both joints and contacts with virtual springs. Methods previously developed for the analysis of force distribution in multiple whole-limb manipulation are generalized to this broader class of mechanisms, and are shown to provide a basis for the control of co-contraction and internal forces that guarantee proper operation of the system. In particular, in the presence of constraints such as those due to limited friction between surfaces or object fragility, the choice of tendon tensions is crucial to the success of manipulation. An algorithm is described that allows to evaluate efficiently set-points for the control of tendon actuators that “optimally” (in a sense to be described) comply with the given constraints.