Mechanical Design and Dynamic Modeling of a Two-Wheeled Inverted Pendulum Mobile Robot

Abstract

The differential drive two-wheeled inverted pendulum mobile robot has advantage of high maneuverability on slopes and in narrow spaces. It can be used to carry human beings as well as other goods. This paper mainly discusses mechanical design and dynamic modeling of this type of mobile robot platform. The first prototype is 12 kg of weight with dimensions of 42x36x15 cm. A multi modal control system is developed which includes the human transport control system and goods transport control system mode. An embedded control system is implemented to control two motors for both modes. In human transport mode the master controller receives the data from the data conditioning module and generates the reference for PID controllers whereas in goods transport mode the master controller receives command from the teleoperator. The effectiveness of the developed mobile robot is confirmed by experiments such as climbing slope, pivot around and surpassing small obstacles.

Fuzzy control based on LMI approach and fuzzy interpretation of the rider input for two wheeled balancing human transporter

“…In which 2 \ is replaced by c. It is observed that equations (12) and (13) form a system containing one input and two outputs. Also, equation (14) describes an independent system which consists of one input and one output.…”

“…It is smaller and lighter in comparison with the Segway. Designed and production of other vehicles similar to Segway has also been reported in literature [10]- [12].…”

“…All of these vehicles applied by and large a similar strategy for moving forward and backward [7]- [12]. When the rider leans forwards, the vehicle accelerates to reach a maximum allowable speed.…”

Nonlinear Autonomous Control of a Two-Wheeled Inverted Pendulum Mobile Robot Based on Sliding Mode

“…A majority of researchers have used either Newton-Euler approach [16], [17] or Langrangian approach [18], [19] to construct the governing mathematics of the system. Newton-Euler method requires calculation of unwanted forces making it less efficient in computation and Langrange method requires Langrange multiplier to be solved which makes the computation complicated.…”

Passivity-Based Control for Two-Wheeled Robot Stabilization

“…The system modeling applies physical laws to derive dynamics equation of a plant. System modeling of a TWR can be done by applying the Newton's laws of motion as presented in [1,2]. TWR modeling by applying the Euler-Lagrange method is presented in [3,4].…”