Since the analytical expressions for the representation of nonrigid object structure and motion are severely underconstrained, current techniques for nonrigid object manipulation employ physical object models known prior to sensing. Recently, however, psychophysical studies have revealed that humans are able to discover proper motor coordination skills through sensory input without the use of previously known physical models. In this paper, a robust, discovery-driven, vision-based robotic manipulation algorithm for nonrigid objects, based on the novel concept of relative elasticity, is developed which requires the use of no a priori physical models. The manipulation technique is also experimentally verified on different flexible linear objects.

A generic kinematics-based design, simulation and control software package called Generic Motion Control (GMC) software has been developed at Philips Laboratories, Briarcliff Manor, New York, USA. It enables automatic generation of control software for robot manipulator systems and diverse industrial automation machines. Functionality provided by the software includes a kinematics description language and compiler for generating symbolically optimized ANSI C control software, a basic kinematics package for performing coordinate transformation, a trajectory generator module for high-level commands, a calibration module for tuning the kinematic model, and a 3D color graphics module and a graphical command interface for simulations. The software is written in the ANSI C programming language and can be installed on a variety of operating systems including Unix and DOS. The following paper focuses on the capabilities and possible applications of the software package in robot control.>

This paper describes a distributed computing and control architecture for experiments in dual-arm sensor-based planning and control. The system comprises of two PUMA 560 robots with state-of-the-art joint-level motion controllers. These controllers have accurate joint position and velocity measurement, an accurate joint calibration system, and six-axis wrist force/torque sensors with optical fiber communication with the controller. A high-power Silicon Graphics workstation, through a shared memory interface with the joint-level controllers, provides a task-level command and control capability. A variety of control schemes can be easily implemented on this system. A servo rate of 1000 Hz, without interpolation, has been achieved for task-level servo schemes with force feedback. The experimental results presented here demonstrate the performance capabilities of the system.>

The problem of rigid object handling by multiple robot arms is investigated. The primary goal is to make the object exhibit a prescribed behavior while in contact with a fully known environment. Point contacts are assumed between the object and the arms. The aspect of task definition to achieve decoupling and linearizing control laws is discussed. Control laws are first formulated at the object level to provide decoupled force and position servo loops. It is then used to form control laws for the individual arms. Redundancies exist at the object and arm levels. The object level redundancy is used to achieve secondary goals in object handling. The arm level redundancies are the zero dynamics and can be controlled by redundant inputs. Full use of the available inputs are used to control the system as a whole. Numerical simulations for a dual-arm situation illustrate the validity of the approach.>

The trajectory tracking performance of the nonlinear feedback controller based on differential geometric control theory was experimentally studied. The performance is compared to three other methods: independent joint proportional-derivative (PD) control, independent joint PD control with feedforward torque computations, and the computed torque method. In the nonlinear feedback controller, servo is in the task space. In the other three methods servo is in the joint space. Path planning is in the task space. Circular and straight line paths are considered. A sampling frequency of 200 Hz is used. The effect of sampling frequency on tracking error is studied for the nonlinear feedback control scheme. The performance of these methods was tested on a PUMA 560 arm. The trajectory tracking performance of the robot arm under the nonlinear feedback controller is comparable to that of the computed torque control schemes.>