Robots can be mathematically modeled with computer programs where the results can be displayed visually, so it can be used to determine the input, gain, attenuate and error parameters of the control system. In addition to the robot motion control system, to achieve the target points should need a research to get the best trajectory, so the movement of robots can be more efficient. One method that can be used to get the best path is the SOM (Self Organizing Maps) neural network. This research proposes the usage of SOM in combination with PID and Fuzzy-PD control for finding an optimal path between source and destination. SOM Neural network process is able to guide the robotmanipulator through the target points. The results presented emphasize that a satisfactory trajectory tracking precision and stability could be achieved using SOM Neural networking combination with PID and Fuzzy-PD controller.The obtained average error to reach the target point when using Fuzzy-PD=2.225% and when using PID=1.965%.
The vertical displacement function  given by the above formula shows an acceleration jump at t = 0, t =T, and a larger contact force is required at the moment of raising the leg. To deal with it, this paper modifies the y-direction displacement equation. I design the trajectory equation that when t = 0 and t = T, the x-direction velocity and acceleration are zero with coordinates of 2
SLAM is an operation, employing an independent robot or an autonomous vehicle, develop or construct a path or track for its climatic or environmental conditions on an uncertain or unclear region on land . At the same time, the autonomous vehicle limits its path or range of area by using the data retrieved before through the route map. At the end of the day, the self-sufficient vehicle attempts to do both mapping and limitation of its track or path simultaneously ,. The EKF SLAM approach to slam is to develop a filtering process for the system . Our work operates on the two-dimensional SLAM in a three-dimensional environment . It adds the carrying believe of having obstacles or having landmarks that are present in the ground plane. The system is modelled in a discrete-time system, with a variable state denoted by a vector known as state vector. The variables in the state vector can change over the motion of the vehicle, hence the system is dynamic. The EKF-SLAM system is like the estimation of a linear dynamic system.
This paper presents Fuzzy-PID controller of a 4 DOF arm robotmanipulator applied in industry. The design started with FLC design to detect the manipulated object. FLC decides robot motion based on color green detection. The mechanical and electronics designs are also presented. Robot motion is simulated by RSTX toolbox in SciLab to checked whether the robot moves as expected. The simulation of robot motion is possible by inputting the DH parameters derived from mechanical design. PID controller is combined with FLC to ensure the motion smoothness and stability
In order to minimise the weight increase associated with the diameter increase, we sought to remove material from the vertebrae while maintaining strength. We therefore con- ducted FEA (Finite Element Analysis) based shape optimisa- tion using the ATOM module in Abaqus (see Fig. 5). Material specifications were taken from the Stratasys website and the boundary conditions were configured to simulate the inter- face between adjacent vertebrae with a torque applied. The optimisation was set up with the Von Mises stress and the volume as the design responses, with the objective function to remove volume while also reducing stress. Critical areas such as the tendon holes and the key/keyway geometry were isolated to prevent volume reduction. This simulation did not take into account the forces from the tendons acting on their guide holes. The optimised geometry was imported into CAD (Computer Aided Design) software and simplified from its abstract shape. The final design for v.1.2 can be seen in Figure 4.
His research interests include: Dynamics of Elastic Me- chanical Manipulators, Trajectory Optimization, Sym- bolic Modeling, Robotic Multimedia Software, Mobile Robots, Industrial Robotics Standard, Robot Vision, Soccer Robot, and the Analysis of Mechanical Manipu- lators with Maximum Load Carrying Capacity. He has published more than 300 papers in international jour- nals and conference proceedings in the eld of robotics. Ehsan Davarzani was born in Tehran, Iran, in 1984. He received his BS degree in Mechanical Engineering from Tehran University in 2007 and his MS degree from the Iran University of Science and Technology in
In the initial phase of the research it needed to be decided which family of paths would be chosen to generate the paths of the trajectories. The decision between parametric and polynomial curves became apparent early on. In the paper ”Time-dependent Motion Planning for Nonholonomic Mobile Robots” they use polynomial curves instead of using Bezier curves due to their approach for introducing timing profiles into the trajectory. In this paper they account for obstacle avoidance and therefor have a set timing for begin and end point, but do not have a strict path that needs to be followed due to this feature. Since the object of this thesis is to have a robot that can emulate targets for a radar detection system and be at a specific time and place with a specific speed, the inclusion of obstacle avoidance and deviation from the set path is completely against the functional requirements of the work.
The changing of system variable (parameters) does not influent the performance of controller (Figure 5). That is shown by the same of time response and steady state error of the system. The change of control input value is to keep the system on the steady state condition. If comparing with the previous research, backstepping adaptive control has been applied with the same plant , the simulation result for the reference position 45 O the system need 2 second to achieve the goal position with 0.5 degree steady state error and still have overshoot. The result of proposed method is better then backstepping adaptive control as previous research. Another previous research, Design of Adaptive Sliding Mode Controller for Robotic Manipulators Tracking Control  shown that performance is still affected by external disturbance.
Dynamic analysis of two DoF parallel manipulator is used to investigate joint clearances of the manipulator joints in investigation of XuLi-xin and LiYong-gang. Trajectories of the end effector for both ideal and clearance joints are calculated in computer and then the results are plotted to observe difference on the end effector trajectory. A new measuring mechanism is designed and tested for zero offset calibration of a similar 2-DoF parallel robotmanipulator by Jiangping et. al. Results of calibration mechanism are illustrated and discussed in plots.
specific target from an initial starting point, avoiding obstacles, and staying within manipulator capabilities. Planning in joint space is the simplest and fastest, because inverse kinematics is avoided. The shortcoming is that the end effector posture is not directly controlled, and hence collision avoidance is challenging. Planning in Cartesian space allows being met the geometric constraints of the external world, but only after solving inverse kinematics. Two algorithms were developed to test the trajectory tracking based on positional analysis.
The paper focuses on the problem of point-to-point trajectoryplanning for flexible redundant robot manip- ulators (FRM) in joint space. Compared with irredundant flexible manipulators, a FRM possesses additional possibil- ities during point-to-point trajectoryplanning due to its kinematics redundancy. A trajectoryplanning method to minimize vibration and/or executing time of a point-to-point motion is presented for FRMs based on Genetic Algorithms (GAs). Kinematics redundancy is integrated into the presented method as planning variables. Quadrinomial and quintic polynomial are used to describe the segments that connect the initial, intermediate, and final points in joint space. The trajectoryplanning of FRM is formulated as a problem of optimization with constraints. A planar FRM with three flexible links is used in simulation. Case studies show that the method is applicable.
A final feature of the algorithm is the implementation of a deadlock handling mechanism. The robot enter a situation in which obstacles block a direct path to the final goal and such obstacles are too large for long-range sensors to plan a path around, the fuzzy algorithm presented thus far could result in oscillatory motion that does not result in progress toward the goal. In such situations, the robot needs a strategy breaking the cycle of unproductive decisions. Typically, this is handled with a wall (or contour) following behavior until a safe trajectory is discovered. The infrared sensors in Koala (6-wheeled) robot are used as both long- and short-range detectors by setting their thresholds accordingly. Experimental results are divided into those for static versus dynamic environments. In a static environment, the algorithm determines only reachable way-points. Graphs of sensor readings show that the readings are generally low except when a way-point is close to the vertex of an obstacle. This behavior is interpreted as the algorithm‟s ability to avoid obstacles before coming close to them. Further, this behavior represents avoidance of the shortsighted behavior problem associated with a purely reactive fuzzy controller. The algorithm‟s behavior in a dynamic environment involves movement of obstacles during the robot‟s passage so as to render some way-points unreachable.
ABSTRACT: This paper relates to a Robot that belongs to the category of Joint Robot.In the article,we analyze the path planning and control system of the robot,specifically speaking,it involves the interpolation of the robottrajectory, the analysis of the inverse kinematics, the introduction of the method to reduce the trajectory error, the optimization of the trajectory and in the end, the corresponding control system is designed according to the relevant parameters. This research project first introduces the importance of the robot, and then analyzes the whole process of the robot from the grasping pin, the screw to they are delivered to the designated position,finally, the process is introduced in detail, and the simulation result is displayed.
In this paper a simulink based approach is developed for trajectory tracking of robotmanipulator. A robotmanipulator is widely used in many industrial application.A robotmanipulator moves the end effector to the configuration instructed by the user. The input from the main unit is transformed in to the desired configuration through forward kinematics. This configuration is sent to the robot controller to transform the configuration into joint angles. The simulink model is developed to provide basic block to model kinematics and trajectory tracking of robotmanipulator. Availability of such library model of robotmanipulator software, where the manipulator controller can be modelled using model library blocks and production can be automatically generated using existing code generators for simulink. In this the desired and the actual trajectory of the end effector under different conditions is shown with the help of MATLAB simulation.
model and mathematical model of the robot that is presented here can perform such hazardous and disgusting works in shortest time with one time investment without any annoying behavior. Yet, there should be in need of a monitoring body who will check the performance and workability of such robots for providing proper maintenance. If this robot can get implemented, then the environmental pollution will get reduced to a great instant indeed.
PSO-PID controller is built and implemented in matlab / simulink software package and it is succeeded to solve the trajectory tracking problem in mobile robot . The Particle Swarm Optimization method is utilized to tune/optimize the parameters of PID controller and its gives us a good results in short time relatively with other optimization methods. Simulation results show good tracking performance with small Mean square error. The resulting good tracking capability and small MSE values show that the proposed method is more effective than other methods such as Ziegler-Nichols method and genetic algorithm approach.
Modelling and simulation of a robot on uneven terrain is of importance as it provides a basis to know about the robots position and its state. In this work we present a simulation framework and dy- namic state space realisation for evolution on uneven terrains for a wheeled mobile robot such as a synchronous drive robot. The framework lends itself as a tool capable of solving various problems, such as forward kinematic based evolution, inverse kinematic based evolution, path planning and trajectory tracking. This framework becomes particularly useful when we understand that the evolution problem (and hence the various associated problems based on evolution) is particularly challenging on uneven terrain. Specifically it is entailed to bring in the contact constraints posed by the interaction of the wheel and the ground as well as the holonomic constraints as the problem is formulated in a DAE setting (Dif- ferential Algebraic Equation). The problem becomes all the more crucial as vehicles moving on uneven terrain are becoming the order of the day. Nonetheless there has not been much literature that deals in length the various aspects that go into the framework. This work elaborates on the various aspects of the framework, presents simulation results on uneven terrain, where the vehicle evolves without slipping and also presents substantial quantitative analysis in regard to wheel slippage.
In the virtual environment, in addition to the robot, a series of obstacles (stones and stairs) were added, as well as an irregular terrain that makes it possible to verify the robot's operation under these conditions and not only the correct operation of the designed programming. Webots allows to make use of controllers designed in MATLAB which allows from the mathematical models of the robot to design control- lers and thus verify their behavior in the virtual environment. In addition to this by using a gamepad, the user is allowed to interact in the virtual environment by control- ling the robot.
In this work several aspects regarding the kinematics, workspace, Jacobian analysis and dynamic identification of a two-link planar manipulator were presented. The results obtained in this study may be useful for the robot designing not only to understand the kinematic behaviour of the robot for various configurations, but also to be able to implement real time control of a manipulator. The programs are developed in C language for generation of workspace points, manipulability index based on Jacobian and for inverse kinematics. The results obtained are plotted separately from data files. Even though the two link manipulator is relatively simple and straight forward, most of the approaches applied here are common to all the manipulators. The static force analysis for obtaining joint torques is a important problem for design of manipulator. Finally the trajectory tracking problem with two different trajectories using CTC control method was illustrated numerically. The errors and corresponding applied torques were shown as a function of time. This two link manipulator analysis and control is an on going work in mechatronics and robotics research.
The MSC. ADAMS software is capable of simulating kinematics and kinetics behaviour of any mechanical system. The dynamic behaviour of a system can be compared with the real models that can be simulated with an acceptable variation in the result . MSC. ADAMS software tool plays very important tool for rapid virtual prototyping which reduces the design failure or feasibility of the design. Real prototype model takes lots of time to test because it needs testing setup and environment. MSC. ADAMS incorporates all the required dynamics virtually which is required for real testing conditions. Various modeling files can be imported in MSC. ADAMS from SolidWorks, Creo, Catia or Solidedge etc. .