Human performers have developed impressive acrobatic techniques over thousands of years of practicing the gymnastic arts. At the same time, robots have started to become more mobile and autonomous, and can begin to imitate these stunts in dramatic and informative ways. We present a simple two degree of freedom robot that uses a gravity-driven pendulum launch and produces a variety of somersaulting stunts. The robot uses an IMU and a laser range-finder to estimate its state mid-flight and actuates to change its motion both on and and off the pendulum. We discuss the dynamics of this behavior in a framework of acrobatic capability and present experimental results.

As agile robots learn to run and hop, we believe they will soon also perform large jumps and spins that require graceful landing. To land properly, they will need to be aware of their relative body orientation during free fall and make appropriate adjustments. In this paper, we examine the sensing and actuation necessary for a mechanism to alter its fall under a high rate of spin. We also present a simple new robot, the Binary Robotic Inertially Controlled bricK (BRICK). This device combines information from an accelerometer, a gyroscope, and a laser range-finder to track its orientation, and adjusts spin mid-flight by rapidly changing its moment of inertia between two states. An error analysis shows mechanical inaccuracies and uncertainty to be the largest source of variation. Nevertheless, our mechanism is able to fall from arbitrary heights, with arbitrary spin, and always land in a desired orientation.

Perching can extend the useful mission life of a micro air vehicle. Once perched, climbing allows it to reposition precisely, with low power draw and without regard for weather conditions. We present the Stanford Climbing and Aerial Maneuvering Platform, which is to our knowledge the first robot capable of flying, perching with passive technology on outdoor surfaces, climbing, and taking off again. We present the mechanical design and the new perching, climbing, and takeoff strategies that allow us to perform these tasks on surfaces such as concrete and stucco, without the aid of a motion capture system or off-board computation. We further discuss two new capabilities uniquely available to a hybrid aerial-scansorial robot: the ability to recover gracefully from climbing failures and the ability to increase usable foothold density through the application of aerodynamic forces. We also measure real power consumption for climbing, flying, and monitoring and discuss how future platforms could be improved for longer mission life.

Perching on a vertical surface carries the risk of severe damage to the vehicle if the maneuver fails, especially if failure goes undetected. We present a detection method using an onboard 3-axis accelerometer to discriminate between perching success and failure. An analytical model was developed to calculate acceleration differences for success and failure and set decision times. Two distinct decision times were shown to be effective, corresponding to properly engaging the gripper and overloading the gripper's capabilities. According to a machine learning feature selection algorithm, the maximum Z axis acceleration of the quadrotor and the presence of near-zero readings are the most relevant features within these two time frames. Using these features, the detection algorithm discriminated between success and failure with a 91% accuracy at 40 ms, and 94% at 80 ms. Real-time detection and failure recovery experiments with a 20 g quadrotor verify the detection method. An improved approach that combines various decision times correctly identified success/failure for all 20 trials with an average total falling distance of 0.8m during recovery. We discuss the feasibility of extending our method to other quadrotor platforms.

Perching allows Micro Aerial Vehicles (MAVs) avoid the power costs and electrical and acoustic noise of sustained flight, for long-term surveillance and reconnaissance applications. This paper presents a dynamic model that clarifies the requirements for repeatable perching on walls and ceilings using an opposed-grip mechanism and dry adhesive technology. The model predicts success for perching over a range of initial conditions. The model also predicts the conditions under which other directional attachment technologies, such as microspines, will succeed. Experiments conducted using a launching mechanism for a range of different landing conditions confirm the predictions of the model and provide insight into future design improvements that are possible by modifying a few key damping and stiffness parameters.

A dynamic model of a jump glider is presented and correlated with the results obtained with a prototype glider. The glider uses a carbon fiber spring and a main wing that pivots approximately parallel to the airflow during ascent and latches into place for a gliding descent. The robot demonstrates longer traveled distance than an equivalent drag-free ballistic mass. A detailed numerical and a simplified algebraic model are also introduced, which are useful for exploring design tradeoffs and performance. These models suggest ways to improve the traveled distance and indicate that with modest variations in the wing angle of attack during ascent, one can choose from a variety of launch angles to accommodate variations in ground friction without greatly compromising range.

Dynamic surface grasping is applicable to landing of micro air vehicles (MAVs) and to grappling objects in space. In both applications, the grasper must absorb the kinetic energy of a moving object and provide secure attachment to a surface using, for example, gecko-inspired directional adhesives. Functional principles of dynamic surface grasping are presented, and two prototype grasper designs are discussed. Computer simulation and physical testing confirms the expected relationships concerning (i) the alignment of the grasper at initial contact, (ii) the absorption of energy during collision and rebound, and (iii) the force limits of synthetic directional adhesives.