The study of animals and insects have led to realization that animals select their gaits, patterns of leg movement, according to speed. For proper gait planning, the legs must be controlled for proper foot placement with respect to the body motion and ground interactions. However, in small scale robotic platforms gait planning through foot placement control is neither cost effective nor easily attainable due to a lack of available sensors. Thus, even though a desired gait is envisioned at the design phase, it is not known whether the gait is optimum. In this work, we present the comprehensive dynamic model of the miniature foldable robot, MinIAQ-II, which has four independently actuated legs. Dynamic model is used to perform gait analysis, to investigate the difference between the intended gait and the achieved gait in the absence of foot placement control. The model is verified through slow speed walking experiments on flat terrain. The work presented can be modified for different miniature robots with passive legs to predict their locomotion under no foot placement control.

Full autonomy remains a challenge for miniature robotic platforms due to mass and size requirements of on-board power and control electronics. This paper presents a solution to these challenges with a 2.3g autonomous legged robot. An off-the-shelf optical mouse sensor is adapted for use on the Harvard Ambulatory Microrobot (HAMR) by reducing the sensor weight by 36% and achieving a position error below 11% when suspended 3mm above a cardstock surface. The position data is combined with data from a gyroscope for feedback control of both position and orientation. A microcontroller processes the sensor data and commands a controlled gait to HAMR that is powered by a battery, a boost converter and high voltage drive electronics. Solar cells are used as an alternative source providing enough power for autonomous operation of the robot. The resulting deviation for a controlled straight-line walk using both sensors to minimize lateral deviation and angular error is only 4.6%, compared to an error of 31% in an uncontrolled, straight-line walk.

Mesoscale robots are devices with characteristic dimensions in the centimeter to millimeter scale, with feature sizes ranging from millimeters to micrometers. Due to the physics involved in scaling down conventional motors, such robots frequently require novel approaches to actuation. Actu- ation can have a very significant effect on robot performance, particularly at small scales where locomotion becomes ener- getically expensive; however, existing options for small-scale actuation are quite limited. We present a mesoscale voice coil actuator (VCA) with favorable scaling characteristics and a design that minimizes costly frictional effects at small scales while allowing fast, linear, high-displacement motion. The VCA is fabricated using planar manufacturing techniques, making it well-suited for integration into a number of mesoscale robotic platforms and for mass production. The designed VCA has a mass of 310mg, maximum force of 11.8mN, bandwidth of 51Hz, and a stroke of 4mm.

Onboard power remains a major challenge for miniature robotic platforms. Locomotion at small scales demands high power densities from all system components, while limited payload capacities place severe restrictions on the size of the energy source, resulting in integration challenges and short operating times when using conventional batteries. Wireless power delivery has the potential to allow microrobotic platforms to operate autonomously for extended periods when near a transmitter. This paper describes the first demonstration of RF wireless power transfer in an insect-scale ambulatory robot. A wireless power transmission system based on magnetically coupled resonance is designed for the latest iteration of the Harvard Ambulatory MicroRobot (HAMR), a piezoelectrically driven quadruped that had previously received power through a tether. Custom power and control electronics are designed and implemented on lightweight printed circuit boards that form a part of the mechanical structure of the robot. The integration of the onboard receiver, power and control electronics, and mechanical structure yields a 4cm, 2.1g robot that can operate autonomously in two wireless power transmission scenarios.

Transmission and actuator selection are crucial for robot locomotion at any scale. This is especially true at small scales where actuation choices are limited and locomotion is energetically expensive. These components control the payload capacity and determine the height of the obstacles the robot can navigate over. In this study, we analyze the drivetrain of the new Harvard Ambulatory MicroRobot (HAMR-V) to improve its walking performance. We modeled several transmission and actuator design concepts and investigated their force and displacement outputs. The results led to the selection of improved actuator and transmission designs. Using these new insights, we constructed a miniature quadruped with a payload capacity of 63% of its weight that can be used for on-board electronics for sensing, control, and power.

Insect-scale legged robots have the potential to locomote on rough terrain, crawl through confined spaces, and scale vertical and inverted surfaces. However, small scale implies that such robots are unable to carry large payloads. Limited payload capacity forces miniature robots to utilize simple control methods that can be implemented on a simple onboard microprocessor. In this study, the design of a new version of the biologically-inspired Harvard Ambulatory MicroRobot (HAMR) is presented. In order to find the most suitable control inputs for HAMR, maneuverability experiments are conducted for several drive parameters. Ideal input candidates for orientation and lateral velocity control are identified as a result of the maneuverability experiments. Using these control inputs, two simple feedback controllers are implemented to control the orientation and the lateral velocity of the robot. The controllers are used to force the robot to track trajectories with a minimum turning radius of 55 mm and a maximum lateral to normal velocity ratio of 0.8. Due to their simplicity, the controllers presented in this work are ideal for implementation with on-board computation for future HAMR prototypes.

In recent years, Model Driven Software Development (MDSD) became new trend in software industry shifting the focus toward problem domain, supporting platform independent solutions and automating software development process. This paper presents a model driven software development approach to be used in a modern military command and control system. The purpose of this approach is to improve design principles such as variability, extensibility and flexibility.

Water strider insects have attracted many researchers' attention with their power efficient and agile water surface locomotion. This study proposes a new water strider insect inspired robot, called STRIDE II, which uses new circular footpads for high lift, stability, payload capability, and a new elliptical leg rotation mechanism for more efficient water surface propulsion. The lift, drag and propulsion forces and the energy efficiency of this robot are modeled and experiments are conducted to verify these models. A maximum lift capacity of 53 grams is achieved with a total of 12 footpads, each 4.2 cm in diameter for a robot weighing 21.75 grams. For this robot, a propulsion efficiency of 22.3% is measured. Maximum forward and turning speeds of the robot are measured as 71.5 mm/sec and 0.21 rad/sec, respectively. These water strider robots could be used in water surface monitoring, cleaning, and analysis in lakes, dams, rivers and sea.

Atomic force microscope (AFM) based nanomanipulation systems are generally slow, not repeatable and imprecise due to a lack of control on the success of limited attempts in the literature. To improve the amount of control, reliability and precision of such systems, this work proposes an automated nanomanipulation method. Spherical gold nanoparticles with 100 nm diameter are positioned mechanically on a flat mica substrate by contact manipulation by the AFM probe tip to a desired position autonomously. The most significant issue of the manipulation operation is the lack of real-time visual feedback. This issue is solved by developing a robust algorithm for particle center detection and using the AFM cantilever deflection (force) signals to detect contact losses in real-time and to repeat the manipulation again until the target location is reached. Using these solutions, an automated AFM manipulation system is developed and a statistical study is made, where gold nanoparticles are positioned for 50 times to random target positions in different directions and pushing distances. 86% of all the particles could be successfully positioned to the target positions with an accuracy less than 100 nm. Unsuccessful positioning operations are due to the particle sticking to either the tip (8%) or the substrate (6%). Additionally, performance of the successful manipulations are investigated on 60 manipulation operations in 12 different directions and 5 different distances. The metrics used to quantify performance are the final particle position error and the average manipulation speed.