Quadrotor-Based Lighthouse Localization with Time-Synchronized Wireless Sensor Nodes and Bearing-Only Measurements.

Some robotic localization methods, such as ultra wideband localization and lighthouse localization, require external localization infrastructure in order to operate. However, there are situations where this localization infrastructure does not exist in the field, such as robotic exploration tasks. Deploying low power wireless sensor networks (WSNs) as localization infrastructure can potentially solve this problem. In this work, we demonstrate the use of an OpenWSN network of miniaturized low power sensor nodes as localization infrastructure. We demonstrate a quadrotor performing laser-based relative bearing measurements of stationary wireless sensor nodes with known locations and using these measurements to localize itself. These laser-based measurements require little computation on the WSN nodes, and are compatible with state-of-the-art 2 mm × 3 mm monolithic wireless system-on-chips (SoCs). These capabilities were demonstrated on a Crazyflie quadcopter using an Extended Kalman Filter and a network of motes running the OpenWSN wireless sensor network stack. The RMS error for X positioning was 0.57 m and the error for Y positioning was 0.39 m. This is the first use of an OpenWSN sensor network to support robotic localization. Furthermore, simulations show that these same measurements could be used for localizing sensor motes with unknown locations in the future.

MEMS-Actuated Carbon Fiber Microelectrode for Neural Recording.

Microwire and microelectrode arrays used for cortical neural recording typically consist of tens to hundreds of recording sites, but often only a fraction of these sites are in close enough proximity to firing neurons to record single-unit activity. Recent work has demonstrated precise, depth-controllable mechanisms for the insertion of single neural recording electrodes, but these methods are mostly only capable of inserting electrodes which elicit an adverse biological response. We present an electrostatic-based actuator capable of inserting individual carbon fiber microelectrodes which elicit minimal to no adverse biological response. The device is shown to insert a carbon fiber recording electrode into an agar brain phantom and can record an artificial neural signal in saline. This technique provides a platform generalizable to many microwire-style recording electrodes.

A high-density carbon fiber neural recording array technology.

OBJECTIVE: Microwire and Utah-style neural recording arrays are the predominant devices used for cortical neural recording, but the implanted electrodes cause a significant adverse biological response and suffer from well-studied performance degradation. Recent work has demonstrated that carbon fiber electrodes do not elicit this same adverse response, but these existing designs are not practically scalable to hundreds or thousands of recording sites. We present technology that overcomes these issues while additionally providing fine electrode pitch for spatial oversampling. APPROACH: We present a 32-channel carbon fiber monofilament-based intracortical neural recording array fabricated through a combination of bulk silicon microfabrication processing and microassembly. This device represents the first truly two-dimensional carbon fiber neural recording array. The density, channel count, and size scale of this array are enabled by an out-of-plane microassembly technique in which individual fibers are inserted through metallized and isotropically conductive adhesive-filled holes in an oxide-passivated microfabricated silicon substrate. MAIN RESULTS: Five-micron diameter fibers are spaced at a pitch of 38 microns, four times denser than state of the art one-dimensional arrays. The fine diameter of the carbon fibers affords both minimal cross-section and nearly three orders of magnitude greater lateral compliance than standard tungsten microwires. Typical [Formula: see text] impedances are on the order of hundreds of kiloohms, and successful in vivo recording is demonstrated in the motor cortex of a rat. 22 total units are recorded on 20 channels, with unit SNR ranging from 1.4 to 8.0. SIGNIFICANCE: This is the highest density microwire-style electrode array to date, and this fabrication technique is scalable to a larger number of electrodes and allows for the potential future integration of microelectronics. Large-scale carbon fiber neural recording arrays are a promising technology for reducing the inflammatory response and increasing the information density, particularly in neural recording applications where microwire arrays are already used.

TDMA-based dual-mode communication for mobile wireless sensor networks.

Small highly mobile robots, and in particular micro air vehicles (MAVs), are well suited to the task of exploring unknown indoor environments such as buildings and caves. Such a task imposes a number of requirements on the underlying communication infrastructure, with differing goals during various stages of the mission. This work addresses those requirements with a hybrid communications infrastructure consisting of a stationary mesh network along with the mobile nodes. The combined network operates in two independent modes, coupling a highly efficient, low duty cycle, low throughput mode for routing and persistent sensing with a burst mode for high data rate communication. By strategically distributing available frequency channels between the mobile agents and the stationary nodes, the overall network provides reliable long-term communication paths while maximizing data throughput when needed.

Wireless inertial sensors for monitoring animal behavior.

Wireless sensors were designed which are small and light enough to be worn by small animals such as rats. These sensors are used to record three axes acceleration data from animals during natural behavior in a cage. The behavior of the animal is further extracted from the recorded acceleration data using neural network based pattern recognition algorithms. Successful recognition of eating, grooming and standing are demonstrated using this approach. Finally another potential application of this research is demonstrated in behavioral neuroscience by showing correlations between action potentials recorded from the motor cortex of a rat and acceleration data.