This paper reports on the existing robot force control algorithms and their composition based on the review of 75 papers on this subject. The objective is to provide a pragmatic exposition with speciality on their differences and different application conditions, and to give a guide of the existing robot force control algorithms. The previous work can be categorized into discussion, design and/or application of fundamental force control techniques, stability analysis of the various control algorithms, and the advanced methods. Advanced methods combine the fundamental force control techniques with advanced control algorithms such as adaptive, robust and learning control strategies.

Current mobile robot ultrasonic localisation techniques use sensor systems which rely on features in a horizontal plane. The implicit assumption is that the room boundary on the horizontal plane is not obstructed by objects such as furniture. This assumption is often not realistic and restricts the versatility and portability of these systems. The solution proposed in this paper is the provision of sensing flexibility to use other 3D room boundaries (e.g. ceiling-wall intersections) as 3D natural beacons. We propose a 3D ultrasonic sensor array that uses a Maximum Likelihood Estimator to match the echo arrival times to different object classes and to determine the location of the 3D target. This method does not require fast data acquisition or powerful computing. It has been implemented on a robot localisation application with the Extended Kalman Filter. This paper is the first of two parts, and presents theoretical results on target classification and minimum transducer requirements. The second part, in the next issue of Robotica, presents experimental results on the characterisation of the sensor and its application to robot localisation, and includes the references for the both papers.

A new real-time obstacle avoidance method for mobile robots has been developed. This method, namely the vector-distance function method, permits the detection of obstacles (both moving and stationary) and generates a path that can avoid collisions. The proposed approach expresses the distance information in a vector form. Then the notion of weighting is introduced to describe relationship between sensors of mobile robots and the target to be reached. Furthermore, R-mode, L-mode and T-mode are introduced to generate a safe path for the mobile robot in a dynamic environment filled with both stationary and moving obstacles. The algorithm can deal with a complicated obstacle environment, such as multiple concave and convex obstacles. Simulation results are included to demonstrate the applicability and effectiveness of the developed algorithm.

The paper deals with the modelling of unknown objects and location determination of known ones. The operator models objects using data issued from the video image and a time of flight infra red range finder. We present methods to build an embodying volume for unknown objects. These methods are available for polyhedral and conical objects, which represent the basis of most industrial environments. The location determination of known objects is determined using 2D clues obtained through video image. A two-step algorithm is implemented and assessed. The first step is available in case of object large motion, it is a geometric algorithm, which doesn't use redundant data; it provides a first estimate of the pose. The second step is available in case of object small motion. A linear approach is carried out to determine the pose. It allows the use of redundant data, so it improves the accuracy achieved after the first step.

In this paper a model to cover all possible topologies of robot manipulators composed of prismatic and revolute joints is presented. For simplicity, only planar systems are considered, hence to provide plane positioning, systems handled are of three degrees of freedom. The physical model assumes three moving rigid links in articulation with one revolute and one prismatic joint between each link pair, forming a six degrees of freedom open chain linkage. Among each joint pair, one is real and the other fictitious. The real joint is arbitrarily actuated by an externally applied force or torque while the fictitious one is acted upon by an appropriately controlled force or torque as to keep that joint velocity zero, keeping fixed at its initial position. The physical model is accompanied by a mathematical model obtained by Lagrange formulation. This approach is called ‘The method of Fictititous Degrees of Freedom’.

In this paper, the development of a fuzzy logic control algorithm for walking machine leg control is presented. The planetary gear leg is designed for a quadruped which can walk and trot under the following design criteria: high efficiency, compact size and high payload/weight ratio. The inverse kinematics and dynamics of this leg are first analysed. A fuzzy logic control algorithm is then developed and implemented to control this prototype leg. The controller controls the leg using position control when the foot is in the air and force control when the foot is on the ground. This fuzzy logic control algorithm is evaluated in both simulation and experiments. A comparison of the proposed control algorithm with the conventional impedance control is given. Results show that the fuzzy logic controller is effective in controlling the leg machine.

This paper presents a novel time-optimal motion planning strategy for a mobile robot with kinematic constraints. The method works in environments in presence of obstacles, without needing to generate the configuration space for the robot. Further, it derives a minimum time first derivative smooth path, as opposed to a minimum distance path which is commonly given by various present solution techniques. The problem is solved in three stages: (i) A reduced visibility graph for a point object is obtained. (ii) The reduced visibility graph is converted into a feasible reduced visibility graph accounting for the size and kinematic constraints of the robot. (iii) The A* algorithm is used to search the feasible reduced visibility graph with the cost function being the time of travel, to obtain a safe, time-optimal, smooth path. The algorithm runs in polynomial time. The method has been tested in computer simulations and test results are presented

In this paper the minimum cost trajectory planning problem with fixed time in robot manipulators is considered. The task is solved by transforming the problem to a set of free right-end time optimal problems, leading to a suboptimal solution. Each problem of the optimal cost trajectory planning with a free time is effectively solved by the method of minimal neighbourhood. An algorithm for the task of suboptimal cost trajectory planning with fixed time is presented and applied to the model of a PUMA-like robot. Results of the paper seem to be of particular relevance to the optimization of multi-robot systems.

This paper describes the experimental evaluation of three identification schemes to determine the dynamic parameters of a two degrees of freedom direct-drive robot. These schemes involve a recursive estimator while the regression models are formulated in continuous time. The fact that the total energy of robot manipulators can be represented as a linear relation in the inertial parameters, has motivated the suggestion in the literature of several regression models which are linear in a common dynamic parameter vector. Among them, in this paper we consider the schemes based on the filtered dynamic regression model, the supplied energy regression model and a new one proposed in this paper: the filtered power regression model. The underling recursive parameter estimator used in the experimental evaluation is the standard least-squares.

In this paper, we propose a two-loop structure to transform and stabilize the kinematic model of a nonholonomic mobile robot with two independently driven wheels. This two-loop structure consists of input-output pseudolinearization and gain scheduling techniques. A comparison with previous methods is included. The main contribution of this paper is to apply a input-output pseudolinearization transformation method and to use an effective pole-assignment strategy for stabilizing a mobile robot with two independently driven wheels. The proposed method has demonstrated superiority over previous methods.

Several descriptions of redundancy are presented in the literature, often from widely different perspectives. Therefore, a discussion of these various definitions and the salient points would be appropriate. In particular, any definition and redundancy needs to cover the following issues; the difference between multiple solutions and an infinite number of solutions; degenerate solutions to inverse kinematics; task redundancy; and the distinction between non-redundant, redundant and highly redundant manipulators.