Decentralized PID self-tuning control of industrial robots

A three degrees of freedom industrial robot is controlled by applying PID self-tuning (PID/ST) controllers. This control is considered as a corrective term to a nominal value, centrally computed from an inaccurate and/ or simplified dynamic model. An identification scheme on an assumed linear plant describing the deviation from the desired trajectory is employed in order to tune the controller coefficients and thus accomplish a behaviour prescribed through a desired pole placement. A salient feature of our approach is the decentralized nature of the controllers producing the corrective term for each joint. This opens the way to practical implementation, as recent computing requirement calculations for similar set-ups have shown in the literature. Numerical results are presented.

Intact automatic imitation of human and robot actions in autism spectrum disorders

The existence of a specialized imitation module in humans is hotly debated. Studies suggesting a specific imitation impairment in individuals with autism spectrum disorders (ASD) support a modular view. However, the voluntary imitation tasks used in these studies (which require socio-cognitive abilities in addition to imitation for successful performance) cannot support claims of a specific impairment. Accordingly, an automatic imitation paradigm (a ‘cleaner’ measure of imitative ability) was used to assess the imitative ability of 16 adults with ASD and 16 non-autistic matched control participants. Participants performed a prespecified hand action in response to observed hand actions performed either by a human or a robotic hand. On compatible trials the stimulus and response actions matched, while on incompatible trials the two actions did not match. Replicating previous findings, the Control group showed an automatic imitation effect: responses on compatible trials were faster than those on incompatible trials. This effect was greater when responses were made to human than to robotic actions (‘animacy bias’). The ASD group also showed an automatic imitation effect and a larger animacy bias than the Control group. We discuss these findings with reference to the literature on imitation in ASD and theories of imitation.

Chaos in high performance digital robot controllers

Active robot force control requires some form of dynamic inner loop control for stability. The author considers the implementation of position-based inner loop control on an industrial robot fitted with encoders only. It is shown that high gain velocity feedback for such a robot, which is effectively stationary when in contact with a stiff environment, involves problems beyond the usual caveats on the effects of unknown environment stiffness. It is shown that it is possible for the controlled joint to become chaotic at very low velocities if encoder edge timing data are used for velocity measurement. The results obtained indicate that there is a lower limit on controlled velocity when encoders are the only means of joint measurement. This lower limit to speed is determined by the desired amount of loop gain, which is itself determined by the severity of the nonlinearities present in the drive system.

Joint servoing for robust manipulator force control

An experimental and theoretical comparison is made of force control performance with different types of innerloop joint servoing techniques. The problem of disturbance rejection and sensitivity to plant dynamics variations (robustness) is addressed. Position, velocity, strain gauge derived joint torque, and current servos are designed and implemented on a specially instrumented industrial robot, and the end-effector force feedback performances achieved are compared. Joint strain derived torque servoing is found to provide the best overall robust force control performance. Experimental results of the robust hard-on-hard contact achieved with the novel force controller implementation based on joint torque sensing are provided. Conclusions are drawn on the force control performance achievable on a geared robot given the joint servoing technique.

Simulation of a diffusion driven mobile robot

In this paper, we investigate the possibility to control a mobile robot via a sensory-motory coupling utilizing diffusion system. For this purpose, we implemented a simulation of the diffusion process of chemicals and the kinematics of the mobile robot. In comparison to the original Braitenberg vehicle in which sensorymotor coupling is tightly realised by hardwiring, our system employs the soft coupling. The mobile robot has two sets of independent sensory-motor unit, two sensors are implemented in front and two motors on each side of the robot. The framework used for the sensory-motor coupling was such that 1) Place two electrodes in the medium 2) Drop a certain amount of Chemical U and V related to the distance to the walls and the intensity of the light 3) Place other two electrodes in the medium 4) Measure the concentration of Chemical U and V to actuate the motors on both sides of the robot. The environment was constructed with four surrounding walls and a light source located at the center. Depending on the design parameters and initial conditions, the robot was able to successfully avoid the wall and light. More interestingly, the diffusion process in the sensory-motor coupling provided the robot with a simple form of memory which would not have been possible with a control framework based on a hard-wired electric circuit.