In this paper, a mode-switching sliding controller with the nonlinear gain generated by a fuzzy logic controller is put forward to enhance the tracking performance in an electro-pneumatic position control system which includes four solenoid ON-OFF valves and a double rod-end cylinder. The proposed method is designed to increase the response speed and reduce the overshoots by utilizing the nonlinear gain which is determined by a fuzzy logic controller. In addition, several improvements are made in the mode-switching sliding controller originally from previous works. The mode-switching strategy is totally redesigned and a hysteresis control scheme is introduced to the new mode-switching sliding controller. Moreover, the improved controller is properly combined with the fuzzy nonlinear gain. Simulation and experiments with various kinds of input are carried out to verify the effectiveness of the proposed method. All the experiments are conducted on a field programmable gate array platform, and the experimental results validate the reliability of the novel scheme.

Visual-tactile sensors that use a camera to capture the deformation of a soft gel layer have become popular in recent years. However, these sensors have a limited receptive field, which can hinder their ability to perceive tactile information effectively. In this letter, we propose a novel visual-tactile sensor named GelFinger that closely resembles the human finger and is well-suited for detecting various complex surfaces. The GelFinger sensor is equipped with an embedded miniature motor that allows for the adaptation of the camera pose and the scanning of a large contact area. During the detection process, the camera rotates to multiple angles to capture the tactile image of the contact area. To stitch together the tactile images obtained at different camera poses, we use an As-Projective-As-Possible image stitching algorithm to form a global view of the contact. We demonstrate the effectiveness of the GelFinger sensor in assessing large surfaces by using it to reconstruct curved crack outlines. Comparative experimental results show that the proposed sensor can effectively detect cracks and has the potential to assist humans in detecting defects on curved surfaces of infrastructure such as pipelines.

Tactile sensing is an essential capability for a robot to perform manipulation tasks in cluttered environments. While larger areas can be assessed instantly with cameras, Lidars, and other remote sensors, tactile sensors can reduce their measurement uncertainties and gain information of the physical interactions between the objects and the robot end-effector that is not accessible via remote sensors. In this paper, we introduce the novel tactile sensor GelTip that has the shape of a finger and can sense contacts on any location of its surface. This contrasts to other camera-based tactile sensors that either only have a flat sensing surface, or a compliant tip of a limited sensing area, and our proposed GelTip sensor is able to detect contacts from all the directions, like a human finger. The sensor uses a camera located at its base to track the deformations of the opaque elastomer that covers its hollow, rigid, and transparent body. Because of this design, a gripper equipped with GelTip sensors is capable of simultaneously monitoring contacts happening inside and outside its grasp closure. Our extensive experiments show that the GelTip sensor can effectively localize these contacts at different locations of the finger body, with a small localization error of approximately 5 mm on average, and under 1 mm in the best cases. Furthermore, our experiments in a Blocks World environment demonstrate the advantages, and possibly a necessity, of leveraging all-around touch sensing in manipulation tasks. In particular, the experiments show that the contacts at different moments of the reach-to-grasp movements can be sensed using our novel GelTip sensor.

In this paper, a fuzzy logic based volume flow control method is proposed to precisely control the force of a pneumatic actuator in an electro-pneumatic system including four on-off valves. The volume flow feature, which is the relationship between the duty cycle of the pulse width modulation (PWM) period, pressure difference, and volume flow of an on-off valve, is based on the experimental data measured by a high-precision volume flow meter. Through experimental data analysis, the maximum and minimum duty cycles are acquired. A new volume flow control method is introduced for the pneumatic system. In this method, the raw measured data are innovatively processed by a segmented, polynomial fitting method, and a newly designed procedure for calculating the duty cycle is adopted. This procedure makes it possible to combine the original data with fuzzy logic control (FLC). Additionally, the method allows us to accurately control the minimum and maximum opening pulse width of the valve. Several experiments are performed based on the experimental data, instead of the traditional theoretical models. Only 0.141 N (1.41%) overshoot and 0.03 N (0.03%) steady-state error are observed in the step response experiment, and 0.123 N average error is found while tracking the sine wave reference.