A real-time obstacle avoidance algorithm is proposed for autonomous mobile robots. The algorithm is sensor-based and consists of a H-mode and T-mode. The algorithm can deal with a complicated obstacle environment, such as multiple concave and convex obstacles. It will be shown that the algorithm is more efficient and more robust than other sensor-based algorithms. In addition, the algorithm will guarantee a solution for the obstacle avoidance problem. Since the algorithm only takes up a small computational time, it can be implemented in real time.

To facilitate expedient communication with robots, a very-high level hierarchical robot command language (HIROB) has been designed and implemented. HIROB uses the full and comprehensive syntax of the English imperative, allowing users to control a robot without the need of learning an esoteric programming language. A Parser/Scanner/Recognizer (PSR) performs a lexical analysis of a HIROB command stream, and identifies which portions of the command stream already exist as fully defined procedures in the files of the Procedure Management System (PMS). Those portions which do not exist must be defined using either existing HIROB procedures (English phrases), or by using the primitive commands of the low-level robot command language (LOROB). This process is fully recursive, so that HIROB procedures may consist of defined or undefined HIROB procedures, as well as LOROB commands, with the understanding that a high-level command cannot be executed until all of its hierarchical sub-commands have been fully defined. A user-friendly editor has been incorporated into the PMS to allow convenient creation, modification, and testing of HIROB commands.

An extension of the inverse kinematics algorithm by Gupta and Kazerounian is presented. The robot kinematics is formulated by using the Zero Reference Position Method. Euler parameters and the related vector forms of the spatial rotation concatenation have been used to improve the efficiency of the velocity Jacobian computation. The joint rates are formally integrated by using a modified predictor-corrector method particularized to robot inverse kinematics – it is a strict descending, p(1)c(0 – n), variable step algorithm. The definitions of the rotational error and overall error measure have been revised. Depending upon the convergence criteria used, these modifications reduce the overall computational time by 20%.

The dynamic model of a new class of underwater robot is derived and the validity of the model is checked experimentally. Close agreements between theory and experiment are attained. The interaction between the buoyancy and gravity forces acting on the robot arm, present in the underwater environment, is used to generate torques necessary to move the arm. The mathematical model of a multi-arm robot is developed to define the interaction between the dynamics of the moving weight and the robot links under the action of the resisting water drag and other external forces. The Lagrangian method is used in the formulation of the arm dynamics. The developed dynamic equations serve as means for designing the control laws necessary for controlling the position of the different joints of the robots. The study indicates that the buoyancy and gravity-driven robot can position a payload accurately as well as at a fairly fast speed of response. It is indicated from the theoretical and experimental study that the arm motion is created by a small displacement of moving weight on the power screw. Therefore, power requirement of this type of robot is just as enough to overcome the friction between the power screw and the moving weight. This features emphasize the potential of the concept as a viable means for driving underwater robots

The complex model presented in this paper consists of three main parts: (a) a model of the robot; (b) tools for building and displaying models of workpieces to be painted; (c) a model of the spatial distribution of the paint particles. The simulation process is preceded by the creation of the surface to be coated. A colour graphic display is used for this purpose. The surface appears on the screen together with the robot (hidden line elimination is included). The “spray gun” is installed at the robot's tip and its orientation, performance and other characteristics are to be set. The paint particles sprayed are supposed to form a cone, and by considering its intersection with the surface, the amount of paint delivered to any point can be evaluated and visualized in different colours. The operator simulates the process of painting by moving the spray gun, changing the parameters (speed, distance, etc.), erasing and repeating any step of the process. He can also work in an automatic path generation mode. The result is a near-to-optimal path of the robot's tip (minimizing paint loss and providing a good evenness of coating).

We discuss the use of fuzzy set based methodologies as a tool for helping robots develop and implement plans. We are particularly concerned with matching fuzzily described states with fuzzy antecedents in production rules.

In standard classical kinematic and dynamic considerations the equations of motion for an n-link manipulator can be obtained as recursive Newton-Euler equations. Another approach to finding the inverse dynamics equations is to formulate the system dynamics and kinematics as a two-point boundary-value problem. The equivalence between these two approaches has been proved in this paper. Solution to the two-point boundary-value problem leads to the forward dynamics equations which are similar to the equations of Kalman filtering and Bryson-Frazier fixed time-interval smoothing. The extensive numerical studies conducted by the author on the new inverse and forward dynamics algorithms derived from the two-point boundary-value problem establish the same level of confidence as exists for current methods. In order to obtain the algorithms with the smallest coefficients of the polynomial of order O(n), the categorization procedure has been implemented in this work.