A technique for open-loop minimum time planning of time-histories of control torques for robotic manipulators subject to constraints on the control torques using evolutionary algorithm is presented here. Planning is carried out in joint space of the manipulator and the path is represented as a string of via-points connected by cubic spline polynomial functions. Repeated path modification is done by using the evolutionary algorithm to search for a time-optimal path. Time taken to traverse over a particular path is calculated by reducing the dynamic equations of motion over that path in terms of a path parameter and then calculating the time optimal-control over that path.

This paper presents a systematic approach to the time-optimal motion planning of a cooperative two robot system along a prescribed path. First, the minimum-time motion planning problem is formulated in a concise form by parameterizing the dynamics of the robot system through a single variable describing the path. The constraints imposed on the input actuator torques and the exerted forces on the object are then converted into those on that variable, which result in the so-called admissible region in the phase plane of the variable. Considering the load distribution problem that is also involved in the motion, we present a systematic method to construct the admissible region by employing the orthogonal projection technique and the theory of multiple objective optimization. Especially, the effects of viscous damping and state-dependent actuator bounds are incorporated into the problem formulation so that the case where the admissible region is not simply connected can be investigated in detail. The resultant time-optimal solution specifies not only the velocity profile, but also the force assigned to each robot at each instant. Physical interpretation on the characteristics of the optimal actuator torques is also included with computer simulation results.

Structural and control flexibilities affect the absolute precision of serial manipulators. A semi-flexible kinematic model is developed, to improve the absolute static precision. It expands the solid body model by incorporating a spring effect for each joint and a beam effect for each link. The identifiability of the added parameters and the effect of measurement noise are explored on a R4 robot. It requires efforts and pose errors to be known in the tool frame only. Simulation results show that identification of some of the parameters is sensitive to measurement noise on forces and pose. In fact, joint flexibility displacement and beam flexion that occur in the same plane are difficult to dissociate in noisy condition. However, a subset of the original parameters can be defined leading to a model that can be more accurately identified when measurement noise is present. In simulation, precompensation is used in an inverse semi-flexible model that results in a 98% decrease of pose error compared to the rigid body inverse geometric model.

We have suggested a novel approach to autonomously navigate a full sized autonomous vehicle that separately treats vehicle control and obstacle detection. In this paper we discuss the vehicle control that has enabled our autonomous vehicle to travel at speeds upto 20mph. We point out the limitations of existing schemes that restrict their consideration to kinematic models and show that it is possible to obtain an increase in performance through the use of approximate dynamical models that capture first–order effects. Our approach combines such a modeling philosophy with accurate feedback in world coordinates from sensors that have only recently become available. Experimental results of our implementation on NavLab, a modified van at CMU, are presented.

Prawns are a significant marine resource in Australia and elsewhere, but their processing after the harvest is a very labour-intensive operation. Every prawn is presently hand packed. The possibility of utilising machine vision and robots to automate this operation has been investigated. Experiments indicate that machine vision can classify prawns into mass-related categories better than people now do, and that prawn orientation can be determined by this means. Although at the present state of technology it appears infeasible for robots to make up the multi-layer fixed-weight packs of prawns as is now done manually, a change to single-layer variable-weight packs should allow this process to be automated and would offer significant advantages to the Australian industry.

This paper deals with the problems of the education of the staff in robotics and flexible automation at the secondary school level. It deals with an experiment which aims at training technicians for robotics and flexible manufacturing systems. The experiment began in 1989. and now the second generation of students that studies according to the curricula of this experiment has completed the education. Previous experience, especially from the standpoint of the result of the students and problems that arise during the realization of the experiment, are analyzed in this text.