Stanley S. Baek

Efficient resonant drive of flapping-wing robots

Flapping-wing air vehicles can improve efficiency by running at resonance to reduce inertial costs of accelerating and decelerating the wings. For battery-powered, DC motor-driven systems with gears and cranks, the drive torque and velocity is a complicated function of battery voltage. Hence, resonant behavior is not as well defined as for flapping-wing systems with elastic actuators. In this paper, we analyze a resonant drive to reduce average battery power consumption for DC motor-driven flapping-wing robots. We derive a nondimensionalized analysis of the generic class of a motor-driven slider crank, considering motor and battery resistance. This analysis is used to demonstrate the benefits of efficient resonant drive on a 5.8g flapping-wing robot and experiments showed a 30% average power reduction by integrating a tuned compliant element.

Flight control for target seeking by 13 gram ornithopter

Recent advances in small-scale flapping-wing micro aerial vehicles have extended the capabilities of flight control for a number of applications, such as intelligence, surveillance, and reconnaissance activities. In this work, we demonstrate autonomous flight control of a 13 gram ornithopter capable of flying toward a target without remote assistance. For autonomous flight control, we developed 1.0 gram control electronics integrated with a microcontroller, inertial and visual sensors, communication electronics, and motor drivers. We also developed a simplified aerodynamic model of ornithopter flight to reduce the order of the control system. With the aerodynamic model and the orientation estimation from on-board inertial sensors, we present flight control of an ornithopter capable of flying toward a target using onboard sensing and computation only. To this end, we developed a dead-reckoning algorithm to recover from the temporary loss of the target which can occur with a visual sensor with a narrow field of view. As a result, the 28 cm wing-span ornithopter flying toward a target landed within a radius of 0.5 m from the target with more than 85% success (N = 20).

MEDIC: A legged millirobot utilizing novel obstacle traversal

This work presents the design, fabrication, capabilities, and obstacle traversal mechanics of MEDIC (Millirobot Enabled Diagnostic of Integrated Circuits), a small legged robot able to overcome a varied array of obstacles. MEDIC features a hull that keeps its body in contact with the ground at all times, and uses only four actuators to move forward, turn, mount obstacles, and move in reverse. The chassis is fabricated using a Smart Composite Microstructures (SCM) approach and the robot is actuated by coiled Shape Memory Alloy (SMA). MEDIC also features a camera which will be useful for navigation in the future.

Flight forces and altitude regulation of 12 gram I-Bird

Ornithopter flight forces are typically measured with the body fixed to a force sensor. Here, we demonstrate the identification of free flight aerodynamic forces at a stable equilibrium point of an ornithopter and compare them with the tethered flight aerodynamic forces. For this demonstration, we have developed a closed-loop altitude regulation for the ornithopter using an external camera and custom made onboard electronics. The results show that the tethered aerodynamic force measurement of a 12 gram ornithopter with zero induced velocity underestimates the total flight force by 24.8 mN.

Reducing Contact Resistance Using Compliant Nickel Nanowire Arrays

Electrical contact resistance can be reduced using an array of compliant and conductive nanowires which make a large area of intimate contact with an opposing surface. In this paper, analyses of electrical contact resistance, fabrication methods, and experimental results of contact resistance for compliant nickel nanowires are presented. To analyze, predict, and measure the contact resistance, models of surface contact between an array of conductive nanowires and a spherical tip probe are presented. Then, an estimate of real area of contact from the measured contact resistance is discussed. The fabrication methods elaborate on electroforming nickel fibers using commercially available nano-porous filters. Finally, experimental results of contact resistance between a spherical tip probe and arrays of nickel nanowires as well as the contact resistance between a flat tip probe and arrays of nickel nanowires are presented. From these experimental results, we show resistance reduction by a factor of more than 20 at a load of 10 mN or less, compared to contact with a flat sheet, and a reduction by a factor of 3 using a spherical probe.

Distributed Probabilistic Search and Tracking of Agile Mobile Ground Targets Using a Network of Unmanned Aerial Vehicles

As technologies in digital computation, sensing, wireless and wired communications, embedded systems, and micro-electro-mechanical systems continue to advance in the coming years, it is certain that we will see a variety of distributed sensor networks (DSNs) being deployed in an increasing number of systems such as power distribution systems, engineering structures and buildings, smart homes, environmental monitoring systems, biomedical systems, military systems, and others. In addition, unlike the traditional networks of sensors, the mobility afforded by autonomous systems, embedded systems, and humans who carry smart sensing devices will contribute in creating new and exciting future sensor networks. These future networks of sensors that take advantage of man-machine interactions will also introduce new applications yet unknown to us. In this paper, we present the origin and time line of DSN development, analyze the benefits and challenges of DSNs, and present a mobile sensor network in the form of an unmanned aerial vehicle (UAV) team using distributed mission area probability maps to search and track mobile ground targets. We propose a novel update strategy for the probability map used by UAVs to store probability information of dynamic target locations in the search area. Two update laws are developed to accommodate maps with different scales. Simulation results are used to demonstrate the validity of the proposed probability-map update strategy.

Optimal path planning of a target-following fixed-wing UAV using sequential decision processes

In this work, we consider the optimal path of a fixed-wing unmanned aerial vehicle (UAV) tracking a mobile surface target. One of the limitations of fixed-wing UAVs in tracking mobile targets is the lack of hovering capability when the target moves much slower than the minimum UAV speed, requiring the UAV maintain an orbit about the target. In this paper, we propose a method to find the optimal policy for fixed-wing UAVs to minimize the location uncertainty of a mobile target. Using a grid-based Markov Decision Process (MDP), we use an off-line policy iteration algorithm to find an optimal UAV path in a coarse discretized state space, followed by an on-line policy iteration algorithm that applies a finer grid MDP to the region of interest to find the final optimal UAV trajectory. We validate the proposed algorithm using computer simulations. Comparing the simulation results with other methods, we show that the proposed method has up to 13% decrease in error uncertainty than ones resulted using conventional methods.

Maximizing target detection under sunlight reflection on water surfaces with an autonomous unmanned aerial vehicle

Reflected sunlight can significantly impact vision-based object detection and tracking algorithms, especially ones based on an aerial platform operating over a marine environment. Unmanned aerial systems above a water surface may be unable to detect objects on the water surface due to sunlight glitter. Although the area affected by sunlight reflection may be limited, rapid course corrections of unmanned aerial vehicles (UAVs)-especially fixed-wing UAVs-is also limited by aerodynamics, making it challenging to determine a reasonable path that avoids sunlight reflection while maximizing chances to capture a target. In this paper, we propose an approach for autonomous UAV path planning that maximizes the accuracy of the estimated target location by minimizing the sunlight reflection influences.

Maximizing Water Surface Target Localization Accuracy Under Sunlight Reflection with an Autonomous Unmanned Aerial Vehicle

Reflected sunlight can significantly impact the effectiveness of vision-based object detection and tracking algorithms, especially ones developed for an aerial platform operating over a marine environment. These algorithms often fail to detect water surface objects due to sunlight glitter or rapid course corrections of unmanned aerial vehicles (UAVs) generated by the laws of aerodynamics. In this paper, we propose a UAV path planning method that maximizes the stationary or mobile target detection likelihood during localization and tracking by minimizing the sunlight reflection influences. In order to better reduce sunlight reflection effects, an image-based sunlight reflection reception adjustment is also proposed. We validate our method using both stationary and mobile target tracking tests.

Exploring the Exponentially Decaying Merit of an Out-of-Sequence Observation

It is well known that in a Kalman filtering framework, all sensor observations or measurements contribute toward improving the accuracy of state estimation, but, as observations become older, their impact toward improving estimations becomes smaller to the point that they offer no practical benefit. In this paper, we provide an practical technique for determining the merit of an old observation using system parameters. We demonstrate that the benefit provided by an old observation decreases exponentially with the number of observations captured and processed after it. To quantify the merit of an old observation, we use the filter gain for the delayed observation, found by re-processing all past measurements between the delayed observation and the current time estimate, a high cost task. We demonstrate the value of the proposed technique to system designers using both nearly-constant position (random walk) and nearly-constant velocity (discrete white-noise acceleration, DWNA) cases. In these cases, the merit (that is, gain) of an old observation can be computed in closed-form without iteration. The analysis technique incorporates the state transition function, the observation function, the state transition noise, and the observation noise to quantify the merit of an old observation. Numerical simulations demonstrate the accuracy of these predictions even when measurements arrive randomly according to a Poisson distribution. Simulations confirm that our approach correctly predicts which observations increase estimation accuracy based on their delay by comparing a single-step out-of-sequence Kalman filter with a selective version that drops out-of-sequence observations. This approach may be used in system design to evaluate feasibility of a multi-agent target tracking system, and when selecting system parameters including sensor rates and network latencies.