  Perception in robot manipulation has been actively explored with the goal of
advancing and integrating vision and touch for global and local feature
extraction. However, it is difficult to perceive certain object internal
states, and the integration of visual and haptic perception is not compact and
is easily biased. We propose to address these limitations by developing an
active acoustic sensing method for robot manipulation. Active acoustic sensing
relies on the resonant properties of the object, which are related to its
material, shape, internal structure, and contact interactions with the gripper
and environment. The sensor consists of a vibration actuator paired with a
piezo-electric microphone. The actuator generates a waveform, and the
microphone tracks the waveform's propagation and distortion as it travels
through the object. This paper presents the sensing principles, hardware
design, simulation development, and evaluation of physical and simulated
sensory data under different conditions as a proof-of-concept. This work aims
to provide fundamentals on a useful tool for downstream robot manipulation
tasks using active acoustic sensing, such as object recognition, grasping point
estimation, object pose estimation, and external contact formation detection.
