Brent Griffin

Resonant wireless power transfer to ground sensors from a UAV

Wireless magnetic resonant power transfer is an emerging technology that has many advantages over other wireless power transfer methods due to its safety, lack of interference, and efficiency at medium ranges. In this paper, we develop a wireless magnetic resonant power transfer system that enables unmanned aerial vehicles (UAVs) to provide power to, and recharge batteries of wireless sensors and other electronics far removed from the electric grid. We address the difficulties of implementing and outfitting this system on a UAV with limited payload capabilities and develop a controller that maximizes the received power as the UAV moves into and out of range. We experimentally demonstrate our prototype wireless power transfer system by using a UAV to transfer nearly 5W of power to a ground sensor.

Preliminary walking experiments with underactuated 3D bipedal robot MARLO

This paper reports on an underactuated 3D bipedal robot with passive feet that can start from a quiet standing position, initiate a walking gait, and traverse the length of the laboratory (approximately 10 m) at a speed of roughly 1 m/s. The controller was developed using the method of virtual constraints, a control design method first used on the planar point-feet robots Rabbit and MABEL. For the preliminary experiments reported here, virtual constraints were experimentally tuned to achieve robust planar walking and then 3D walking. A key feature of the controller leading to successful 3D walking is the particular choice of virtual constraints in the lateral plane, which implement a lateral balance control strategy similar to SIMBICON. To our knowledge, MARLO is the most highly underactuated bipedal robot to walk unassisted in 3D.

Walking gait optimization for accommodation of unknown terrain height variations

We investigate the design of periodic gaits that will also function well in the presence of modestly uneven terrain. We use parameter optimization and, inspired by recent work of Dai and Tedrake, augment a cost function with terms that account for perturbations arising from a finite set of terrain height changes. Trajectory and control deviations are related to a nominal periodic orbit via a mechanical phase variable, which is more natural than comparing solutions on the basis of time. The mechanical phase variable is also used to penalize more heavily deviations that persist “late” into the gait. The method is illustrated both in simulation and in experiments on a planar bipedal robot.

From 2D Design of Underactuated Bipedal Gaits to 3D Implementation: Walking With Speed Tracking

Analysis and controller design methods abound in the literature for planar (also known as 2-D) bipedal models. This paper takes one of them developed for underactuated bipeds and documents the process of designing a family of controllers on the basis of a planar model and achieving stable walking on a physical 3-D robot, both indoors and outdoors, with walking speed varying smoothly from 0 to 0.8 m/s. The longest walk in a single experiment is 260 m over terrain with ±7° of slope variation. Advantages and disadvantages of the design approach are discussed.

Experimental results for 3D bipedal robot walking based on systematic optimization of virtual constraints

Feedback control laws which create asymptotically stable periodic orbits for hybrid systems are an effective means for realizing dynamic legged locomotion in bipedal robots. To address the challenge of designing such control laws, we recently introduced a method to systematically select a stabilizing feedback control law from a parameterized family of feedback laws by solving an offline optimization problem. The method has been used elsewhere to design a stable gait based on virtual constraints, and its potential effectiveness was illustrated via simulation results. In this paper, we present the first experimental demonstration of a controller designed using this new offline optimization method. The new controller is compared with a nominal controller in experiments on MARLO, a 3D point-foot bipedal robot. Compared to the nominal controller, the optimized controller leads to improved lateral control and longer sustained walking.

Nonholonomic virtual constraints for dynamic walking

Virtual constraints are functional relations (i.e., constraints) on the state variables of a robots model that are achieved through the action of actuators and feedback control instead of physical contact forces. They are called virtual because they can be re-programmed on the fly without modifying any physical connections among the links of the robot or its environment. Previous analytical and experimental work has established that vector relative degree two virtual holonomic (i.e., only configuration dependent) constraints are a powerful means to synchronize the links of a bipedal robot so as to achieve walking and running motions over a variety of terrain profiles. This paper introduces a class of virtual nonholonomic constraints that depend on velocity through (generalized) angular momentum while maintaining the property of being relative degree two. This additional freedom is shown to yield control solutions that handle a wider range of gait perturbations arising from terrain variations and exogenous forces. Moreover, including angular momentum in the virtual constraints allows foot placement control to be rigorously designed on the basis of the full dynamic model of the biped, instead of on the basis of an inverted pendulum approximation of its center of mass, as is commonly done in the bipedal robotics literature. This new class of control laws is shown in simulation to be robust to a variety of common gait disturbances.

Experimental Analysis of a UAV-Based Wireless Power Transfer Localization System

Sensors deployed in remote locations provide unprecedented amounts of data, but powering these sensors over long periods remains a challenge. In this paper, we develop and present a UAV-based wireless power transfer system. We discuss design considerations and present our system that allows a UAV to fly to remote locations to charge hard to access sensors. We analyze the impact of different materials on the wireless power transfer system. Since GPS does not provide sufficient accuracy, we develop and experimentally characterize a relative localization algorithm based on sensing the magnetic field of the power transfer system and optical flow that allows the UAV to localize the sensor with an average error of 15 cm to enable the transfer of on average 4.2 W. These results overcome some of the practical challenges associated with wirelessly charging sensors with a UAV and show that UAVs with wireless power transfer systems can greatly extend the life of remotely deployed sensors.

Omni-directional hovercraft design as a foundation for MAV education

Quad-rotor Micro Aerial Vehicles (MAVs) are used widely in research and increasingly in commercial applications as the cost of these platforms has dropped. The cost of entry, however, is still high in large part due to the time and effort involved in repairing vehicles after crashes while learning about the system design and dynamics. In this paper, we present an omni-directional hovercraft, which has dynamics similar to MAVs and can be used as an educational platform to teach students about the behavior and control of MAV-like platforms with minimal cost and effort. Teaching students about the capabilities and challenges associated with MAVs is critical for educating future engineers and scientists that will develop and use the next generation of MAVs. In addition, the hovercraft provides a safe platform for researchers to test control and coordination algorithms before trying them on higher-cost MAVs.

Nonholonomic virtual constraints and gait optimization for robust walking control

A key challenge in robotic bipedal locomotion is the design of feedback controllers that function well in the presence of uncertainty, in both the robot and its environment. This paper addresses the design of feedback controllers and periodic gaits that function well in the presence of modest terrain variation, without over-reliance on perception and a priori knowledge of the environment. Model-based design methods are introduced and subsequently validated in simulation and experiment on MARLO, an underactuated three-dimensional bipedal robot that is of roughly human size and is equipped with an inertial measurement unit and joint encoders. Innovations include an optimization method that accounts for multiple types of disturbances and a feedback control design that enables continuous velocity-based posture regulation via nonholonomic virtual constraints. Using a single continuously defined controller taken directly from optimization, MARLO traverses sloped sidewalks and parking lots, terrain covered with randomly thrown boards, and grass fields, all while maintaining average walking speeds between 0.9 and 0.98 m/s and setting a new precedent for walking efficiency in realistic environments.

Unmanned Aerial Vehicle-Based Wireless Charging of Sensor Networks

Sensor networks deployed in remote and hard to access locations often require regular maintenance to replace or charge batteries as solar panels are sometimes impractical. In this chapter, we develop an Unmanned Aerial Vehicle (UAV) that can fly to remote locations to charge sensors using magnetic resonant wireless power transfer. We discuss the challenges of using UAVs to charge sensors wirelessly. We then present the design of a lightweight system that can be carried by a UAV as well as design a localization sensor and algorithm to allow the UAV to precisely align itself with the receiver by sensing the induced field. We also develop a number of algorithms to address the question of which sensors should be charged given a network of sensors. Finally, we experimentally verify algorithms that leverage the sensor network’s ability to adapt internal communication and energy consumption patterns to optimize UAV-based wireless charging.