This paper proposes a computationally efficient, novel and superior nonlinear controller to the existing trajectory and orientation (T& O) control problem of an omnidirectional robot (ODR). Here first, the position and orientation (pose) estimation of the robot were obtained utilizing kinematic relationships of the ODR and multi-sensor fusion techniques. Then, dynamic relationships of the robot were used to form its state-space representation. The nonlinear state-space representation (NLSSR) was linearized by identifying and controlling the nonlinearity causing states. Then that linearized NLSSR was utilized to derive a state feedback controller and a proportional derivative integral (PID) controller to carry out a T& O tracking task. Performances of both derived controllers were evaluated in the simulation level comparing with a standard nonlinear controller. From the two proposed controllers, the best-performing, state feedback-based controller was able to be successfully implemented on a low-cost hardware platform due to its computational efficiency.