Adaptive backstepping position control of pneumatic anthropomorphic robotic hand

This paper presents a nonlinear adaptive backstepping algorithm for position control of an anthropomorphic robotic hand. The contraction force of PAM actuator has been modeled based on an empirical approach and the overall finger is represented as a nonlinear second order system, taking into account the system uncertainty caused by hysteresis phenomenon in PAM actuators. Adaptive backstepping controller has been developed by formulating the estimator of the system uncertainty. To improve the performance of controller, a cascade control system is developed by combining a conventional PID control, as an inner loop controller, with the adaptive back stepping position control as the outer loop of the controller. Finally, a simulation test is conducted to evaluate the performance of the proposed controller

CUSTOMIZABLE SOFT PNEUMATIC GRIPPER DEVICES

Master'sMASTER OF ENGINEERIN

Improving robotic grasping system using deep learning approach

Traditional robots can only move according to a pre-planned trajectory which limits the range of applications that they could be engaged in. Despite their long history, the use of computer vision technology for grasp prediction and object detection is still an active research area. However, the generating of a full grasp configuration of a target object is the main challenge to plan a successful robotic operation of the physical robotic grasp. Integrating computer vision technology with tactile sensing feedback has given rise to a new capability of robots that can accomplish various robotic tasks. However, the recently conducted studies had used tactile sensing with grasp detection models to improve prediction accuracy, not physical grasp success. Thus, the problem of detecting the slip event of the grasped objects that have different weights is addressed in this research. This research aimed to develop a Deep Learning grasp detection model and a slip detection algorithm and integrating them into one innovative robotic grasping system. By proposing a four-step data augmentation technique, the achieved grasping accuracy was 98.2 % exceeding the best-reported results by almost 0.5 % where 625 new instances were generated per original image with different grasp labels. Besides, using the twostage- transfer-learning technique improved the obtained results in the second stage by 0.3 % compared to the first stage results. For the physical robot grasp, the proposed sevendimensional grasp representations method allows the autonomous prediction of the grasp size and depth. The developed model achieved 74.8 milliseconds as prediction time, which makes it possible to use the model in real-time robotic applications. By observing the real-time feedback of a force sensing resistor sensor, the proposed slip detection algorithm indicated a quick response within 86 milliseconds. These results allowed the system to maintain holding the target objects by an immediate increase of the grasping force. The integration of the Deep Learning and slip detection models has shown a significant improvement of 18.4% in the results of the experimental grasps conducted on a SCARA robot. Besides, the utilized Zerocross-Canny edge detector has improved the robot positioning error by 0.27 mm compared to the related studies. The achieved results introduced an innovative robotic grasping system with a Grasp-NoDrop-Place scheme

Scaled Autonomy for Networked Humanoids

Humanoid robots have been developed with the intention of aiding in environments designed for humans. As such, the control of humanoid morphology and effectiveness of human robot interaction form the two principal research issues for deploying these robots in the real world. In this thesis work, the issue of humanoid control is coupled with human robot interaction under the framework of scaled autonomy, where the human and robot exchange levels of control depending on the environment and task at hand. This scaled autonomy is approached with control algorithms for reactive stabilization of human commands and planned trajectories that encode semantically meaningful motion preferences in a sequential convex optimization framework. The control and planning algorithms have been extensively tested in the field for robustness and system verification. The RoboCup competition provides a benchmark competition for autonomous agents that are trained with a human supervisor. The kid-sized and adult-sized humanoid robots coordinate over a noisy network in a known environment with adversarial opponents, and the software and routines in this work allowed for five consecutive championships. Furthermore, the motion planning and user interfaces developed in the work have been tested in the noisy network of the DARPA Robotics Challenge (DRC) Trials and Finals in an unknown environment. Overall, the ability to extend simplified locomotion models to aid in semi-autonomous manipulation allows untrained humans to operate complex, high dimensional robots. This represents another step in the path to deploying humanoids in the real world, based on the low dimensional motion abstractions and proven performance in real world tasks like RoboCup and the DRC

Advanced Mobile Robotics: Volume 3

Mobile robotics is a challenging field with great potential. It covers disciplines including electrical engineering, mechanical engineering, computer science, cognitive science, and social science. It is essential to the design of automated robots, in combination with artificial intelligence, vision, and sensor technologies. Mobile robots are widely used for surveillance, guidance, transportation and entertainment tasks, as well as medical applications. This Special Issue intends to concentrate on recent developments concerning mobile robots and the research surrounding them to enhance studies on the fundamental problems observed in the robots. Various multidisciplinary approaches and integrative contributions including navigation, learning and adaptation, networked system, biologically inspired robots and cognitive methods are welcome contributions to this Special Issue, both from a research and an application perspective

NASA Tech Briefs, February 1989

This issue contains a special feature on shaping the future with Ceramics. Other topics include: Electronic Components & and Circuits. Electronic Systems, Physical Sciences, Materials, Computer Programs, Mechanics, Machinery, Fabrication Technology, Mathematics and Information Sciences, and Life Sciences

Concept, modeling and experimental characterization of the modulated friction inertial drive (MFID) locomotion principle:application to mobile microrobots

A mobile microrobot is defined as a robot with a size ranging from 1 in3 down to 100 µm3 and a motion range of at least several times the robot's length. Mobile microrobots have a great potential for a wide range of mid-term and long-term applications such as minimally invasive surgery, inspection, surveillance, monitoring and interaction with the microscale world. A systematic study of the state of the art of locomotion for mobile microrobots shows that there is a need for efficient locomotion solutions for mobile microrobots featuring several degrees of freedom (DOF). This thesis proposes and studies a new locomotion concept based on stepping motion considering a decoupling of the two essential functions of a locomotion principle: slip generation and slip variation. The proposed "Modulated Friction Inertial Drive" (MFID) principle is defined as a stepping locomotion principle in which slip is generated by the inertial effect of a symmetric, axial vibration, while the slip variation is obtained from an active modulation of the friction force. The decoupling of slip generation and slip variation also has lead to the introduction of the concept of a combination of on-board and off-board actuation. This concept allows for an optimal trade-off between robot simplicity and power consumption on the one hand and on-board motion control on the other hand. The stepping motion of a MFID actuator is studied in detail by means of simulation of a numeric model and experimental characterization of a linear MFID actuator. The experimental setup is driven by piezoelectric actuators that vibrate in axial direction in order to generate slip and in perpendicular direction in order to vary the contact force. After identification of the friction parameters a good match between simulation and experimental results is achieved. MFID motion velocity has shown to depend sinusoidally on the phase shift between axial and perpendicular vibration. Motion velocity also increases linearly with increasing vibration amplitudes and driving frequency. Two parameters characterizing the MFID stepping behavior have been introduced. The step efficiency ηstep expresses the efficiency with which the actuator is capable of transforming the axial vibration in net motion. The force ratio qF evaluates the ease with which slip is generated by comparing the maximum inertial force in axial direction to the minimum friction force. The suitability of the MFID principle for mobile microrobot locomotion has been demonstrated by the development and characterization of three locomotion modules with between 2 and 3 DOF. The microrobot prototypes are driven by piezoelectric and electrostatic comb drive actuators and feature a characteristic body length between 20 mm and 10 mm. Characterization results include fast locomotion velocities up to 3 mm/s for typical driving voltages of some tens of volts and driving frequencies ranging from some tens of Hz up to some kHz. Moreover, motion resolutions in the nanometer range and very low power consumption of some tens of µW have been demonstrated. The advantage of the concept of a combination of on-board and off-board actuation has been demonstrated by the on-board simplicity of two of the three prototypes. The prototypes have also demonstrated the major advantage of the MFID principle: resonance operation has shown to reduce the power consumption, reduce the driving voltage and allow for simple driving electronics. Finally, with the fabrication of 2 × 2 mm2 locomotion modules with 2 DOF, a first step towards the development of mm-sized mobile microrobots with on-board motion control is made

Development of soft modular robotics

This thesis covers the development and validation of soft robots in providing upper limb assistive motion. The main purpose of this research is to develop highly compliant and resilient actuators that generate motion for elbow and shoulder movements. To accomplish the purpose of the study, the fabrication, geometric construction along with experimental data of pressure, torque and range of motion of all developed actuators are described. The main contribution of this thesis is the development of soft actuators that transfer force via elastic deformation in order to generate assistive motion; features such as flexibility and soft contact with the skin ensure excellent safety potential of the actuators. To reduce the instability phenomenon attributed to the elastic response of rubber under large deformations that leads to bulging, the implementation of a pleated network design and embedded braided mesh network is presented. Bulging was reduced and torque output was increased with the integration of braided mesh into the silicone rubber actuator. The soft actuators developed for elbow and shoulder motion was tested on ten healthy participants thereby demonstrating its comfort, ease of use, fitting and removal as well as its practicality as an assistive apparatus for stroke patients. The use of soft robotics to provide shoulder motion was also assessed by the integration of soft robotics with a gravity compensated exoskeleton. The developed soft actuators were powered with electro-pneumatic hardware components presented in a compact, embedded form. Positive and negative air pressure control was implemented by a piecewise linear control algorithm with the performance of the controller shown. The design of a novel muscle made entirely of silicone rubber that contract upon actuation was described together with the manufacturing procedure, design parameters and measurement results of performance of these muscles such as the velocity of shortening, isometric contraction and maximal obtainable muscle force (without shortening). The muscles are manufactured to mimic the skeletal muscles present in the human body. These muscles are composed of a number of wedge-like units in series, the number of these wedge units increase the contraction. The soft muscles were characterized in order to find optimum design parameters that results in more contraction and speed; the muscles were tested on a model hinge joint to execute flexion/extension of the forearm at the elbow. Aside from contracting, the muscle has an interesting capability of producing bidirectional bending by the regulation of internal positive and negative air pressure in each wedge unit. In order to measure performance data relating to range of motion from bending, rotary and muscle actuators, computer vision processing was made use of. Soft robots are made with materials that experience large deformations, the sensors used to obtain measurement data can either be through the use of embedded sensors or visual processing. The use of embedded sensors can be cumbersome, resulting in limitation of its performance. The visual processing algorithms implemented to measure performance data such as angle of motion, bending angle and contraction ratio in real-time using a Webcam is described. Visual processing concepts such as colour tracking, template matching, camera calibration were applied. The developed vision system was applied to execute vision based motion control which is able to move the soft robot to a desired position using high level vision control and lower level pressure control. The material described in the preceding paragraphs are presented in an interrelated format. A concise introduction to the thesis is presented in the first chapter. An extensive survey of the field of soft robotics including materials, manufacturing procedure, actuation principles, primary accomplishments, control and challenges are presented in the literature review chapter, together with a review of rehabilitation devices. Since this work focused on the use of silicone rubber as actuator material, a brief introduction to working with silicone rubber as an engineering material is presented in the third chapter. The conclusions of the work and suggestions for future research are provided at the last chapter of this thesis