Gary M. Bone

Accurate position control of a pneumatic actuator using on/off solenoid valves

The development of a fast, accurate, and inexpensive position-controlled pneumatic actuator that may be applied to a variety of practical positioning applications is described. A novel pulse width modulation (PWM) valve pulsing algorithm allows on/off solenoid valves to be used in place of costly servo valves. The open-loop characteristic is shown both theoretically and experimentally to be near symmetrical. A comparison of the open- and closed-loop responses of standard PWM techniques and that of the novel PWM technique shows that there has been a significant improvement in the control. A linear process model is obtained from experimental data using system identification. A proportional integral derivative controller with added friction compensation and position feedforward has been successfully implemented. A worst case steady-state accuracy of 0.21 mm was achieved with a rise time of 180 ms for step inputs from 0.11 to 64 mm. Following errors to 64-mm S-curve profiles were less than 2.0 mm. The controller is robust to a sixfold increase in the system mass. The actuators overall performance is comparable to that achieved by other researchers using servo valves.

Nonlinear Modeling and Control of Servo Pneumatic Actuators

Pneumatic actuators are low-cost, safe, clean, and exhibit a high power to weight ratio. In this paper a new modeling approach and control law for pneumatic servo actuators are presented. The nonlinear system model is developed using a combination of mechanistic and empirical methods. The use of novel bipolynomial functions to model the valve flow rates is shown to produce a more accurate solution than prior approaches. A novel multiple-input single-output nonlinear position control law is designed using the backstepping methodology. The stability analysis includes the effects of friction modeling error and valve modeling error. Experiments are conducted with 9.5-mm bore and 6.4-mm bore pneumatic cylinders, and four low-cost two-way proportional valves. In experiments with the 9.5-mm bore cylinder and a 1.5-kg moving mass, maximum tracking errors of plusmn0.5 mm for a 1-Hz sine wave trajectory, and steady-state errors within plusmn0.05 mm for an S-curve trajectory were achieved.

Experimental Comparison of Position Tracking Control Algorithms for Pneumatic Cylinder Actuators

Many researchers have investigated pneumatic servo positioning systems due to their numerous advantages: inexpensive, clean, safe, and high ratio of power to weight. However, the compressibility of the working medium, air, and the inherent nonlinearity of the system continue to make achieving accurate position control a challenging problem. In this paper, two control algorithms are designed for the position tracking problem and their experimental performance is compared for a pneumatic cylinder actuator. The first algorithm is sliding-mode control based on a linearized plant model (SMCL) and the second is sliding-mode control based on a nonlinear plant model (SMCN). Extensive experiments using different payloads (1.9, 5.8, and 10.8 kg), vertical and horizontal movements, and move sizes from 3 to 250 mm were conducted. Averaged over 70 experiments with various operating conditions, the tracking error for SMCN was 18% less than with SMCL. For a 5.8-kg payload and a 0.5-Hz 70-mm amplitude, sine wave reference trajectory, the root-mean-square error with SMCN was less than 0.4 mm for both vertical and horizontal motions. This tracking control performance is better than those previously reported for similar systems.

Vision-guided fixtureless assembly of automotive components

Abstract Assembly operations in many industries make extensive use of fixtures that are costly and inflexible. The goal of “robotic fixtureless assembly” (RFA) is to replace these fixtures with sensor-guided robots. In this paper, the development of a vision-guided RFA workcell for automotive components is described. Each robot is equipped with a multiple degree-of-freedom programmable gripper, allowing it to hold a wide range of part shapes without tool changing. A 2D computer vision is used to achieve part pickup which is robust to positioning errors. A novel 3D computer vision system is used to align the parts prior to joining them. The actions of the workcell devices are coordinated using a flexible distributed object-oriented approach. Experimental results are presented for the RFA of four automotive body components.

Automated modeling and robotic grasping of unknown three-dimensional objects

This paper describes the development of a novel vision-based modeling and grasping system for three-dimensional (3D) objects whose shape and location are unknown a priori. Our approach integrates online computer vision-based 3D object modeling with online 3D grasp planning and execution. A single wrist-mounted video camera is moved around the stationary object to obtain images from multiple viewpoints. Object silhouettes are extracted from these images and used to form a 3D solid model of the object. To refine the model, the objects top surface is modeled by scanning with a wrist-mounted line laser while recording images. The laser line in each image is used to form a 3D surface model that is combined with the silhouette result. The grasp planning algorithm is designed for the parallel-jaw grippers that are commonly used in industry. The algorithm analyses the solid model, generates a robust force closure grasp, and outputs the required gripper position and orientation for grasping the object. The robot then automatically picks up the object. Experiments are performed with two real-world 3D objects, a metal bracket and a hex nut. The shape, position and orientation of the objects are not known by the system a priori. The time required to compute an object model and plan a grasp was less than 4 s for each object. The experimental results demonstrate that the automated grasping system can obtain suitable models and generate successful grasps, even when the objects are not lying parallel to the supporting table.

High steady-state accuracy pneumatic servo positioning system with PVA/PV control and friction compensation

Pneumatic servo actuators have the benefits of low-cost, cleanliness and a high power-to-weight ratio. However, their relatively poor accuracy prevents them from competing with electro-mechanical systems when higher accuracy is needed. The cause of the steady-state error for a pneumatic servo system with an open-center servo valve is investigated. Full nonlinear and linearized plant models are presented. An effective friction compensation method is introduced which can be added to any control strategy. When combined with a novel PVA/PV control approach, a steady-state accuracy of /spl plusmn/0.01mm was verified in experiments. This is a tenfold improvement over previously reported experimental results for such systems. This performance is achieved for both vertical and horizontal movements with payloads ranging from 0.3 to 11.3kg, without re-tuning the controller.

Real-time 3D Collision Avoidance Method for Safe Human and Robot Coexistence

A novel solution to the three-dimensional dynamic human-robot collision problem is presented. Sphere-based geometric models are used for the human and robot due to the efficiency of the distance computation. The collision avoidance algorithm searches for collision-free paths by moving the end-effector along a set of pre-defined search directions. An optimization method is employed to select the search direction that balances between the robot approaching its goal location, and maximizing the distances between the human and robot models. The optimization incorporates predictions of the motions of the robot and human to reduce the negative effects of a non-instantaneous robot time response. The robot prediction is based on a transfer function model of its experimental time response at the joint level. The human prediction is performed at the sphere level using the weighted mean of past velocities. Predicting at the sphere level eliminates the difficulty introduced by the limbs moving in different directions. After describing the collision avoidance algorithm, a human walking towards a moving Puma robot arm is simulated. Captured motion data is used to make the human motion realistic. Monte Carlo simulations using 1000 random human walking paths passing through the robot workspace are used to evaluate the algorithm. The algorithm prevented all collisions due to the robot. The algorithm is deterministic and efficient enough to be used in real-time. On a 1.8 GHz Pentium IV PC, a 40 Hz sampling rate was achieved

Real-Time Process Characterization of Open Die Forging for Adaptive Control

Open die forging is a process in which products are made through repeated, incremental plastic deformations of a workpiece, Typically, the workpiece is held by a manipulator. which can position the workpiece through program control between the dies of a press. The part programs are generated with an empirically derived parameter, called the spread coefficient, whose value is subject to some contention. In this work, we demonstrate how process information can be used in real time to derive the actual spread coefficient for a given workpiece as it is being formed. These measurements and calculations occur in real time, and can be used to regenerate part programs to optimize the forming process, or can be used to adaptively control each incremental deformation of the workpiece.

Multi-metric comparison of optimal 2D grasp planning algorithms

The planning of optimal grasps is an important problem in robotics which has been investigated by many researchers. The large number of available methods has made it difficult to discern those which plan a grasp with good overall performance, i.e., one with high strength, insensitivity to positioning errors, and ease of computation. In this paper, a new grasp planning method is introduced and compared to three existing planning methods using three such metrics. A new metric for measuring the sensitivity of a grasp to positioning errors is also introduced. Since grasp planning is much simpler in 2D, and 2D grasps are applicable to many 3D objects, the four methods involve only a 2D analysis. The methods are applied to a set of six polygonal objects, ranging from 3 sided to 74 sided, and their overall performance is compared. The benchmarking procedure is readily applicable to other grasp planning methods.

Experimental comparison of two pneumatic servo position control algorithms

Many researchers have investigated pneumatic servo positioning systems due to their numerous advantages: inexpensive, clean, safe and high ratio of power to weight. However, the compressibility of the working medium, air, and the inherent non-linearity of the system continue to make achieving accurate position control a challenging problem. In this paper two control algorithms are designed for the pneumatic servo problem and their experimental performance is compared. The first algorithm uses position plus velocity plus acceleration feedback combined with feedfoward and deadzone compensation (PVA+FF+DZC). The second algorithm is a form of sliding-mode control (SMC). Extensive experiments using different payloads (1.9, 5.8 and 10.8 kg), vertical and horizontal movements, and move sizes from 3 to 250 mm were conducted. Averaged over 70 experiments with various operating conditions, the tracking error for SMC was 59% less than with PVA+FF+DZC. For a 5.8 kg payload and a 0.5 Hz, 70 mm amplitude, sine wave reference trajectory the root mean square error with SMC was less than 0.4 mm for both vertical and horizontal motions. This tracking control performance is better than those previously reported for similar systems.