Navigation and Control of Mobile Robot Using Sensor Fusion

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Trajectory tracking and time delay management of 4-mecanum wheeled mobile robots (4-MWMR)

International audienceNowadays, wheeled mobile robots have a very important role in industrial applications, namely in transportation tasks thanks to their accuracy and rapidity. However, meeting obstacles while executing a mission can cause an important time delay, which is not appreciable in industry where production must be optimal. This paper deals with the time delay management, the trajectory generation and the tracking problem applied on four wheeled omnidirectional mobile robots. A strategy is proposed to minimize or compensate the time delay caused by obstacles. The approach is done by updating the reference trajectory. This update helps to track the trajectory in real time, a new control law based on the feedback linearization control theory is synthesized to track perfectly generated or updated trajectories

Gesture Recognition Aplication based on Dynamic Time Warping (DTW) FOR Omni-Wheel Mobile Robot

This project presents of the movement of omni-wheel robot moves in the trajectory obtained from the gesture recognition system based on Dynamic Time Warping. Single camera is used as the input of the system, which is also a reference to the movement of the omni-wheel robot. Some systems for gesture recognition have been developed using various methods and different approaches. The movement of the omni-wheel robot using the method of Dynamic Time Wrapping (DTW) which has the advantage able to calculate the distance of two data vectors with different lengths. By using this method we can measure the similarity between two sequences at different times and speeds. Dynamic Time Warping to compare the two parameters at varying times and speeds. Application of DTW widely applied in video, audio, graphics, etc. Due to data that can be changed in a linear manner so that it can be analyzed with DTW. In short can find the most suitable value by minimizing the difference between two multidimensional signals that have been compressed. DTW method is expected to gesture recognition system to work optimally, have a high enough value of accuracy and processing time is realtime

Trajectory tracking control based on adaptive neural dynamics for four-wheel drive omnidirectional mobile robots

There is usually the speed jump problem existing in conventional back-stepping tracking control for four-wheel drive omni-directional mobile robots, a trajectory tracking controller based on adaptive neural dynamics model is proposed. Because of the smoothness and boundedness of the output from the neural dynamics model, it produces a gradually varying tracking speed instead of the jumping speed, and the parameters are designed to avoid the control values exceeding their limits. And then, a parameter adaptive controller is presented to improve control performance. Simulation results of different paths and comparison with the conventional back-stepping technique show that the approach is effective, and the system has a good performance with smooth output

Trajectory tracking control based on adaptive neural dynamics for four-wheel drive omnidirectional mobile robots

There is usually the speed jump problem existing in conventional back-stepping tracking control for four-wheel drive omni-directional mobile robots, a trajectory tracking controller based on adaptive neural dynamics model is proposed. Because of the smoothness and boundedness of the output from the neural dynamics model, it produces a gradually varying tracking speed instead of the jumping speed, and the parameters are designed to avoid the control values exceeding their limits. And then, a parameter adaptive controller is presented to improve control performance. Simulation results of different paths and comparison with the conventional back-stepping technique show that the approach is effective, and the system has a good performance with smooth output

Embedded system for motion control of an omnidirectional mobile robot

In this paper, an embedded system for motion control of omnidirectional mobile robots is presented. An omnidirectional mobile robot is a type of holonomic robots. It can move simultaneously and independently in translation and rotation. The RoboCup small-size league, a robotic soccer competition, is chosen as the research platform in this paper. The first part of this research is to design and implement an embedded system that can communicate with a remote server using a wireless link, and execute received commands. Second, a fuzzy-Tuned proportional-integral (PI) path planner and a related low-level controller are proposed to attain optimal input for driving a linear discrete dynamic model of the omnidirectional mobile robot. To fit the planning requirements and avoid slippage, velocity, and acceleration filters are also employed. In particular, low-level optimal controllers, such as a linear quadratic regulator (LQR) for multiple-input-multiple-output acceleration and deceleration of velocity are investigated, where an LQR controller is running on the robot with feedback from motor encoders or sensors. Simultaneously, a fuzzy adaptive PI is used as a high-level controller for position monitoring, where an appropriate vision system is used as a source of position feedback. A key contribution presented in this research is an improvement in the combined fuzzy-PI LQR controller over a traditional PI controller. Moreover, the efficiency of the proposed approach and PI controller are also discussed. Simulation and experimental evaluations are conducted with and without external disturbance. An optimal result to decrease the variances between the target trajectory and the actual output is delivered by the onboard regulator controller in this paper. The modeling and experimental results confirm the claim that utilizing the new approach in trajectory-planning controllers results in more precise motion of four-wheeled omnidirectional mobile robots. 2018 IEEE.Scopu

Comprehensive Development And Control Of A Path-Trackable Mecanum-Wheeled Robot

This paper presents an intuitively straightforward yet comprehensive approach in developing and controlling a Mecanum-wheeled robot (MWR), with decent path tracking performance by using a simple controller as an end objective. The development starts by implementing two computer ball mice as sensors to realize a simple localization that is immune toward wheel slippage. Then, a linearization method by using open-loop step responses is carried out to linearize the actuations of the robot. Open-loop step response is handy, as it directly portrays the non-linearity of the system, thus achieving effective counteraction. Then, instead of creating a lookup table, polynomial regression is used to generate an equation in which the equation later represents an element of the linearizer. Next, a linear angle-to-gain (LA-G) method is introduced for path tracking control. The method is as easy as just linearly maps the summation of two angles-the angle between immediate and desired positions and the MWR's heading angle, into gains to control the wheels. Unlike the conventional control method which involves inverse kinematics, the LA-G method is directly a displacement-controlled approach and does not require the knowledge of parametric values, such as the robot's dimensions and wheel radius. Finally, all the methods are implemented, and the MWR experimentally demonstrates successfully tracking various paths, by merely using proportional controllers

Dynamics of a 9-DOF Heterogeneous Robotic Platform for Spacecraft Motion Emulation

Increasing access to space has driven demand for low cost, portable, and highly specialized robotic platforms to accurately simulate multi-dimensional space missions. Presented is an effective heterogeneous robotic system that emulates orbital motion from given control algorithms. This robotic platform is composed of a three degrees of freedom (3-DOF) holonomic omni wheel ground vehicle carrying a 6-DOF robotic manipulator, which results in a 9-DOF coupled moving manipulator system. The dynamical models are derived and feedback linearization is studied to control the system. The integrated controls and hardware result in an a sophisticated in-lab system that will be scalable from orbital motion to execution of complex tasks, including spaceflight rendezvous and proximity operations, servicing missions, and surface exploration and sampling