Finding optimal paths for robot navigation in a known terrain has been studied for some time but, in many important situations, a robot would be required to navigate in completely new or partially explored terrain. We propose a method of robot navigation which requires no pre-learned model, makes maximal use of available information, records and synthesizes information from multiple journeys, and contains concepts of learning that allow for continuous transition from local to global path optimality. The model of the terrain consists of a spatial graph and a Voronoi diagram. Using acquired sensor data, polygonal boundaries containing perceived obstacles shrink to approximate the actual obstacles surfaces, free space for transit is correspondingly enlarged, and additional nodes and edges are recorded based on path intersections and stop points. Navigation planning is gradually accelerated with experience since improved global map information minimizes the need for further sensor data acquisition. Our method currently assumes obstacle locations are unchanging, navigation can be successfully conducted using two-dimensional projections, and sensor information is precise.

This paper outlines the analysis methodology employed in the design of an anthropomorphic hand for the purposes of object handling by robotic manipulators, and for prosthetics. The final design is described and the safe handling of various objects using this anthropomorphic hand is discussed.

This paper describes an autonomous robot vehicle which can navigate through an initially unknown obstacle field to a nominated goal or systematically map its working environment. The navigation system uses combined ultrasonic beacon/odometry based localisation, optical range finders for environmental mapping, an A path planning procedure and continuous motion control. The computational support is divided between a graphics workstation 'home base' and a PC hosted transputer array on-board. The integration of all the subsystems cited above has been achieved and many successful navigation experiments completed. Possible further developments which would enhance the capabilities of the system are also discussed.

This paper investigates the feasibility of constructing a humanoid robot using existing technology. Firstly, the adoption of the humanoid form is justified. The structure, strength and power capabilities of a human are analysed in engineering terms, and taken to represent the requirements specification for a humanoid robot. Technological alternatives to the biological components are reviewed and compared to this specification. The feasibility of matching human performance is considered, and it is concluded that the necessary power and energy requirements can be fitted within the mass and volume of the human body.

A new type of microrobot is described. Its simple and compact design is believed to be of promise in the microrobotics field. Stepping motion allows speeds up to 4mm/s. Resolution smaller than 10 nm is achievable. Experiments in an open-loop motion demonstrated a repeatability better than 50µm on a 10 mm displacement at an average speed of 0.25 mm/s. A position feedback based on a microvision system will be developed in order to achieve a submicron absolute position accuracy.

A new mathematical formulation of robot and obstacles is presented such that for on-line collision recognition only robot joint positions in the workspace are required. This reduces calculation time essentially because joint positions in workspace can be computed every time from the joint variables through robot geometry. It is assumed that the obstacles in the workspace of the manipulator are represented by convex polygons. For every link of the redundant robot and every obstacle a boundary ellipse is defined in workspace such that there is no collision if the robot joints are outside this ellipsis.

In addition to this, a collision avoidance method is presented which allows the use of redundant degrees of freedom such that a manipulator can avoid obstacles while tracking the desired end-effector trajectory. The method is based on the generalized inverse with boundary ellipse functions as optimization criteria. The method permits the tip of the hand to approach any arbitrary point in the free space while the kinematic control algorithm maximizes the boundary ellipse function of the critical link. The effectiveness of the proposed methods is discussed by theoretical considerations and illustrated by simulations of the motion of three- and four-link planar manipulators between obstacles.

This paper presents two adaptive schemes for controlling the end-effector compliance of robot manipulators. Each controller possesses a decentralized structure, in which the control input for each configuration degree-offreedom (DOF) is computed based on information concerning only that DOF. The first scheme is developed using an adaptive impedance control approach and consists of two subsystems: a simple “filter” which modifies the end-effector position trajectory based on the sensed contact force and the desired dynamic relationship between the position and force, and an adaptive controller that produces the joint torques required to track this modified trajectory. The second compliant motion control strategy is an adaptive admittance controller for position-controlled manipulators. In this scheme a desired contact force is specified and then position setpoints for the “inner-loop” position controller are generated which ensure that this desired force is achieved. The proposed controllers are extremely simple computationally, do not require knowledge of the manipulator dynamic model or parameter values of the manipulator or the environment, and are implemented in decentralized form.