Force Control of a Unilateral Master-Slave System Using a SCARA Robot Arm

Industrial manipulators have several applications in a multitude of disciplines. The use of industrial manipulators has increased rapidly, and they are more refined in many applications due to advances such as fast response time, high precision, quick speed and a high level of performance. Most industrial manipulators are position-controlled; usually vision and force sensors are not integrated in most commercial industrial robots. Therefore, the addition of force and vision sensing mechanisms is required to successfully automate advanced tasks, and to enable robots to avoid high contact forces while working in applications that require contact with environments. The objective of this thesis is to implement a unilateral master-slave system for medical applications. In this thesis, a Polaris Vicra® optical tracking device is used to represent the master system, while a four degree of freedom (DOF) position-controlled SCARA manipulator from Epson is used to represent the slave system. The manipulator is equipped with a force-torque sensor to facilitate operation in unknown environments. In addition, MapleSim is used to find the dynamic model for the SCARA manipulator. Furthermore, MapleSim is also used to validate the control algorithm prior to implementation on the hardware. Three force control techniques are used in this research and the robot's performance are evaluated. The control techniques are impedance control, admittance control and fuzzy logic control. The admittance and fuzzy logic controllers are applied to the proposed master-slave system while the impedance control is applied to the manipulator model, which was obtained from MapleSim. In order to validate the presented control algorithms, several experiments and simulations were carried out. The experimental results show the ability of the presented controllers (admittance and fuzzy logic) to track the operator signal while keeping the force within the desired range. The simulation and animation of the impedance controller on the other hand, shows that the robot's performance can be evaluated through software

Design, Optimization, and Experimental Characterization of a Novel Magnetically Actuated Finger Micromanipulator

The ability of external magnetic fields to precisely control micromanipulator systems has received a great deal of attention from researchers in recent years due to its off-board power source. As these micromanipulators provide frictionless motion, and precise motion control, they have promising potential applications in many fields. Conversely, major drawbacks of electromagnetic micromanipulators, include a limited motion range compared to the micromanipulator volume, the inability to handle heavy payloads, and the need for a large drive unit compared to the size of the levitated object, and finally, a low ratio of the generated magnetic force to the micromanipulator weight. To overcome these limitations, we designed a novel electromagnetic finger micromanipulator that was adapted from the well-known spherical robot. The design and optimization procedures for building a three Degree of Freedoms (DOF) electromagnetic finger micromanipulator are firstly introduced. This finger micromanipulator has many potential applications, such as cell manipulation, and pick and place operations. The system consists of two main subsystems: a magnetic actuator, and an electromagnetic end-effector that is connected to the magnetic actuator by a needle. The magnetic actuator consists of four permanent magnets and four electromagnetic coils that work together to guide the micromanipulator finger in the xz plane. The electromagnetic end-effector consists of a rod shape permanent magnet that is aligned along the y axis and surrounded by an electromagnetic coil. The optimal configuration that maximizes the micromanipulator actuation force, and a closed form solution for micromanipulator magnetic actuation force are presented. The model is verified by measuring the interaction force between an electromagnet and a permanent magnet experimentally, and using Finite Element Methods (FEM) analysis. The results show an agreement between the model, the experiment, and the FEM results. The error difference between the FEM, experimental, and model data was 0.05 N. The micromanipulator can be remotely operated by transferring magnetic energy from outside, which means there is no mechanical contact between the actuator and the micromanipulator. Moreover, three control algorithms are designed in order to compute control input currents that are able to control the position of the end-effector in the x, y, and z axes. The proposed controllers are: PID controller, state-feedback controller, and adaptive controller. The experimental results show that the micromanipulator is able to track the desired trajectory with a steady-state error less than 10 µm for a payload free condition. Finally, the ability of the micromanipulator to pick-and-place unknown payloads is demonstrated. To achieve this objective, a robust model reference adaptive controller (MRAC) using the MIT rule for an adaptive mechanism to guide the micromanipulator in the workspace is implemented. The performance of the MRAC is compared with a standard PID controller and state-feedback controller. For the payload free condition, the experimental results show the ability of the micromanipulator to follow a desired motion trajectory in all control strategies with a root mean square error less than 0.2 mm. However, while there is payload variation, the PID controller response yields a non smooth motion with a large overshoot and undershoot. Similarly, the state-feedback controller suffers from variability of dynamics and disturbances due to the payload variation, which yields to non-smooth motion and large overshoot. The micromanipulator motion under the MRAC control scheme conversely follows the desired motion trajectory with the same accuracy. It is found that the micromanipulator can handle payloads up to 75 grams and it has a motion range of ∓ 15 mm in all axes

Gait Cycle Monitoring System Based on Flexiforce Sensors

Medical technology companies have focused on gait analysis and monitoring for several years due to their importance in the diagnosis of various movement abnormalities. Studying pressure distribution on the foot is very important for the detection of abnormalities, unwanted symptoms, and consequences. This paper aims to design a wearable, low-cost, and real-time gait cycle monitoring system, based on a Flexiforce sensor. In the proposed design, eight force sensors were attached to the insole to estimate the pressure distribution on the foot. Pressure distribution monitoring helps in the estimation of foot disorders and assists in the design of medical shoes for manipulating pressure into the right positions. Sensors were connected to an appropriate microcontroller for real-time monitoring. MATLAB was used to visualize and simulate the real-time plantar pressure variation through static and dynamic states. The obtained experimental results show that the system was stable in both static and dynamic measurements, which could be used to estimate the pressure distribution on the foot

Gait Cycle Monitoring System Based on Flexiforce Sensors

Medical technology companies have focused on gait analysis and monitoring for several years due to their importance in the diagnosis of various movement abnormalities. Studying pressure distribution on the foot is very important for the detection of abnormalities, unwanted symptoms, and consequences. This paper aims to design a wearable, low-cost, and real-time gait cycle monitoring system, based on a Flexiforce sensor. In the proposed design, eight force sensors were attached to the insole to estimate the pressure distribution on the foot. Pressure distribution monitoring helps in the estimation of foot disorders and assists in the design of medical shoes for manipulating pressure into the right positions. Sensors were connected to an appropriate microcontroller for real-time monitoring. MATLAB was used to visualize and simulate the real-time plantar pressure variation through static and dynamic states. The obtained experimental results show that the system was stable in both static and dynamic measurements, which could be used to estimate the pressure distribution on the foot