Dynamics and control of an omnidirectional unmanned ground vehicle

Author(s):  
Imad Khan ◽  
Matthew Spenko
Author(s):  
Zain UI Abdin ◽  
Taimur Islam Khan ◽  
Mazhar Shabir

Author(s):  
Xiaohui Yang ◽  
Jian Zhao

In order to effectively analyse the mirror sliding friction(MSF) degree of unmanned ground vehicle(UGV) and improve its anti-disturbance performance, a simulation method for MSF degree of UGV based on RBF neural network is proposed. A single-input and double-output RBF neural network is adopted to estimate the uncertain dynamic parameters of the MSF model. The obtained parameters are used to describe the MSF control law based on RBF neural network. An adaptive law based on slow time-varying disturbance characteristics is designed to estimate the total friction disturbance term in the MSF model online. The simulation results show that the proposed method can analyse the MSF degree of unmanned ground vehicle at different speeds and gradients. The influence of gradient on the decline rate of friction degree is greater than that of vehicle speed. The mean error of friction disturbance term calculated by the method is only about 0.9% which has the advantage of low error of friction degree estimation when compared to conventional methods.


Author(s):  
Mostafa Salama ◽  
Vladimir V. Vantsevich

This paper presents a project developed at the University of Alabama at Birmingham (UAB) aimed to design, implement, and test an off-road Unmanned Ground Vehicle (UGV) with individually controlled four drive wheels that operate in stochastic terrain conditions. An all-wheel drive off-road UGV equipped with individual electric dc motors for each wheel offers tremendous potential to control the torque delivered to each individual wheel in order to maximize UGV slip efficiency by minimizing slip power losses. As previous studies showed, this can be achieved by maintaining all drive wheels slippages the same. Utilizing this approach, an analytical method to control angular velocities of all wheels was developed to provide the same slippages of the four wheels. This model-based method was implemented in an inverse dynamics-based control algorithm of the UGV to overcome stochastic terrain conditions and minimize wheel slip power losses and maintain a given velocity profile. In this paper, mechanical and electrical components and control algorithm of the UGV are described in order to achieve the objective. Optical encoders built-in each dc motor are used to measure the actual angular velocity of each wheel. A fifth wheel rotary encoder sensor is attached to the chassis to measure the distance travel and estimate the longitudinal velocity of the UGV. In addition, the UGV is equipped with four electric current sensors to measure the current draw from each dc motor at various load conditions. Four motor drivers are used to control the dc motors using National Instruments single-board RIO controller. Moreover, power system diagrams and controller pinout connections are presented in detail and thus explain how all these components are integrated in a mechatronic system. The inverse dynamics control algorithm is implemented in real-time to control each dc motors individually. The integrated mechatronics system is distinguished by its robustness to stochastic external disturbances as shown in the previous papers. It also shows a promising adaptability to disturbances in wheel load torques and changes in stochastic terrain properties. The proposed approach, modeling and hardware implementation opens up a new way to the optimization and control of both unmanned ground vehicle dynamics and vehicle energy efficiency by optimizing and controlling individual power distribution to the drive wheels.


2021 ◽  
Vol 3 (3) ◽  
Author(s):  
Uttam U. Deshpande ◽  
Aditya Barale ◽  
V. S. Malemath

The prime reason for proposing the work is designing and developing a low-cost guided wireless Unmanned Ground Vehicle (UGV) for use in hospitals for assistance in contactless drug delivery in COVID-19 wards. The Robot is designed as per the requirements and technical specifications required for the healthcare facility. After a detailed survey and tests of various mechanisms for steering and structure of UGV, the best mechanism preferred for steering articulated and for body structure is hexagonal as this approach provides decent performance and stability required to achieve the objective. The UGV has multiple sensors onboard, such as a Camera, GPS module, Hydrogen, and Carbon Gas sensor, Raindrop sensor, and an ultrasonic range finder on UGV for the end-user to understand the circumferential environment and status of UGV. The data and control options are displayed on any phone or computer present in the Wi-Fi zones only if the user login is validated. ESP-32 microcontroller is the prime component utilized to establish reliable wireless communication between the user and UGV.These days, the demand for robot vehicles in hospitals has increased rapidly due to pandemic outbreaks as using this makes a contactless delivery of the medicinal drug. These systems are designed specifically to assist humans in the current situation where life can be at risk for healthcare facilities. In addition, the robot vehicle is suitable for many other applications like supervision, sanitization, carrying medicines and medical equipment for delivery, delivery of food and used dishes, laundry, garbage, laboratory samples, and additional supply.


2021 ◽  
Author(s):  
Subhan Khan ◽  
Jose Guivant

Abstract This paper presents a solution for the tracking control problem, for an unmanned ground vehicle (UGV), under the presence of skid-slip and external disturbances in an environment with static and moving obstacles. To achieve the proposed task, we have used a path-planner which is based on fast nonlinear model predictive control (NMPC); the planner generates feasible trajectories for the kinematic and dynamic controllers to drive the vehicle safely to the goal location. Additionally, the NMPC deals with dynamic and static obstacles in the environment. A kinematic controller (KC) is designed using evolutionary programming (EP), which tunes the gains of the KC. The velocity commands, generated by KC, are then fed to a dynamic controller, which jointly operates with a nonlinear disturbance observer (NDO) to prevent the effects of perturbations. Furthermore, pseudo priority queues (PPQ) based Dijkstra algorithm is combined with NMPC to propose optimal path to perform map-based practical simulation. Finally, simulation based experiments are performed to verify the technique. Results suggest that the proposed method can accurately work, in real-time under limited processing resources.


2020 ◽  
Vol 2 (1) ◽  
pp. 28-33
Author(s):  
Safi Ullah Butt ◽  
Abdul Rauf Bhatti ◽  
Bilal Ali ◽  
Ali Bashir ◽  
Muhammad Umar ◽  
...  

This paper presents the design and implementation of unmanned ground vehicle (UGV) using a simple approach. An unmanned ground vehicle is an automobile without any onboard human presence. It is remotely controlled by an operator. It can be used in scenarios where the presence of human operator is inconvenient and dangerous. It is an Arduino and Android application based controlled vehicle. Bluetooth module (HC-06) provides the communication between the vehicle components and Android application. The motion of the vehicle is based on two DC gear motors that are connected to the rear wheels of the vehicle. The vehicle is equipped with the video camera (V380S) and a gun to provide live video stream to the operator and to fire in lethal situations respectively. The developed vehicle shows the possible usage of such prototype in security and military applications.


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