**8. Conclusion**

Multimodal biometrics in the context of human-robot interaction is discussed under different challenges. The most commonly used biometric traits namely face, iris, fingerprint, ear, palmprint, and voice are discussed in this chapter. Various challenges such as pose, illumination, expression, aging variations, and occlusion are explained, and many state-of-the-art biometric systems involving these challenges are presented and compared. The comparison of these systems shows that multimodal biometrics overcomes the limitations of unimodal systems and achieves better person identification performance. Additionally, score-level fusion technique applied on more than one biometric trait obtains higher recognition rates for person identification. On the other hand, fusion of face and speech is an appropriate choice for human-robot interaction, since the enrollment phase of face and speech biometric systems does not require physical or direct contact with sensors. The face image or speech of a person can be captured by a robot, even if the person is far away from the robot.
