Biomimetic smart sensors for autonomous robotic behavior I: acoustic processing
Socrates Deligeorges, Aaron Soloway, Lee Lichtenstein, Tyler Gore, Allyn E. Hubbard
- 发表年份
- 2009
- 引用次数
- 2
摘要
Robotics are rapidly becoming an integral tool on the battlefield and in homeland security, replacing humans in hazardous conditions. To enhance the effectiveness of robotic assets and their interaction with human operators, smart sensors are required to give more autonomous function to robotic platforms. Biologically inspired sensors are an essential part of this development of autonomous behavior and can increase both capability and performance of robotic systems. Smart, biologically inspired acoustic sensors have the potential to extend autonomous capabilities of robotic platforms to include sniper detection, vehicle tracking, personnel detection, and general acoustic monitoring. The key to enabling these capabilities is biomimetic acoustic processing using a time domain processing method based on the neural structures of the mammalian auditory system. These biologically inspired algorithms replicate the extremely adaptive processing of the auditory system yielding high sensitivity over broad dynamic range. The algorithms provide tremendous robustness in noisy and echoic spaces; properties necessary for autonomous function in real world acoustic environments. These biomimetic acoustic algorithms also provide highly accurate localization of both persistent and transient sounds over a wide frequency range, using baselines on the order of only inches. A specialized smart sensor has been developed to interface with an iRobot Packbot® platform specifically to enhance its autonomous behaviors in response to personnel and gunfire. The low power, highly parallel biomimetic processor, in conjunction with a biomimetic vestibular system (discussed in the companion paper), has shown the system's autonomous response to gunfire in complicated acoustic environments to be highly effective.
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