We introduce an optimization-based control approach that enables a team of robots to cooperatively track a target using onboard sensing. In this setting, the robots are required to estimate their own positions as well as concurrently track the target. Our probabilistic method generates controls that minimize the expected future uncertainty of the target. Additionally, our method efficiently rea...

Robot helicopter research at the University of Southern California began in 1991 with the formation of the Autonomous Flying Vehicle (AFV) Project and continues to the present day. During this time our lab has designed, built and conducted research with three robot helicopters. A brief project history and background is given, followed by a more detailed description of the current state and acco...

We describe and explain new advancements in the design of the aerodynamic force platform, a novel instrument that can directly measure the aerodynamic forces generated by freely flying animals and robots. Such in vivo recordings are essential to better understand the precise aerodynamic function of flapping wings in nature, which can critically inform the design of new bioinspired robots. By de...

Robots need autonomous navigation to complete their tasks efficiently. This becomes more challenging in GPS-denied environments where positioning information is not available. For small flying robots and quadrotors, inherent limitations such as limited sensor payload and small system time-constant add another layer of challenge to the problem. This paper presents a solution for autonomous navig...

While mobile robots and walking insects can use proprioceptive information (specialized receptors in the insect's leg, or wheel encoders in robots) to estimate distance traveled, flying agents have to rely mainly on visual cues. Experiments with bees provide evidence that flying insects might be using optical flow induced by egomotion to estimate distance traveled. Recently some details of this...

This paper investigates a novel active-sensing-based obstacle avoidance paradigm for flying robots in dynamic environments. Instead of fusing multiple sensors to enlarge the field view (FOV), we introduce an alternative approach that utilizes stereo camera with independent rotational DOF sense obstacles actively. In particular, sensing direction is planned heuristically by objectives, including...

Three-dimensional models provide a volumetric representation of space which is important for a variety of robotic applications including flying robots and robots that are equipped with manipulators. In this paper, we present an open-source framework to generate volumetric 3D environment models. Our mapping approach is based on octrees and uses probabilistic occupancy estimation. It explicitly r...

Recently, flapping robots are noticed by many researchers, and many challenges are being made toward the realization of flight motions like insects, birds and so on. The purpose of this work is to develop flapping robots using a new type of piezoelectric material, that is, piezoelectric fiber composites. By using the composites, actuating fibers and sensing fibers can be embedded into a wing as...