Generally, eye closure (EC) and eye opening (EO)-based alpha blocking has widely recognized advantages, such as being easy to use, requiring little user training, while motor imagery (MI) is difficult for some users to have concrete feelings. This study presents a hybrid brain-computer interface (BCI) combining MI and EC strategies - such an approach aims to overcome some disadvantages of MI-based BCI, improve the performance and universality of the BCI. The EC/EO is employed to control the machine to switch in different states including forward, stop, changing direction motions, while the MI is used to control the machine to turn left or right for 90° by imagining the hands grasp motions when the system is switched into "changing direction" state. Additionally, a wearable two-channel EEG device is utilized in order to increase the efficiency of EEG processing and improving the practical utility. Results show that proposed hybrid system can generate four control commands with the average accuracy of 87.72%, which is higher than only using MI. Besides, it is possible to reach the same good accuracy using two-channel EEG as with usual multi-channel EEG.