Novel Dihedral-Based Control of Flapping-Wing Aircraft With Application to Perching

Abstract

Abstract-We describe the design of an aerial robot inspired by birds and the underlying theoretical developments leading to novel control and closed-loop guidance algorithms for a perching maneuver. A unique feature of this robot is that it uses wing articulation to control the flight path angle as well as the heading angle. It lacks a vertical tail for improved agility, which results in unstable lateraldirectional dynamics. New closed-loop motion planning algorithms with guaranteed stability are obtained by rewriting the flight dynamic equations in the spatial domain rather than as functions of time, after which dynamic inversion is employed. It is shown that nonlinear dynamic inversion naturally leads to proportionalintegral-derivative controllers, thereby providing an exact method for tuning the gains. The capabilities of the proposed bioinspired robot design and its novel closed-loop perching controller have been successfully demonstrated with perched landings on a human hand.

A Survey on Aerial Swarm Robotics

“…If a linear diffusive coupling is used, τ i would produce L similar to (4). The EulerLagrange equations appear routinely robotics in the study of rigid body motions of manipulators [26], [27] and spacecraft or aircraft (SE(3)), which have attitude dynamics on SO(3) [28]- [30] and often times have articulated wings [14], [31], [32], appendages, or manipulators attached:…”

“…This model is accurate under the assumption that the rotational dynamics (α and µ) are stable and converge rapidly to the commanded value. The 3-D aerial robot model can be used effectively to reduce the computational burden on a motion planning system and generate trajectories that are optimal, stable, and safe (i.e., with collision avoidance) [14], [33]. In [34], model-based control laws were derived, together with a collision-avoiding system, for a swarm of parafoilpayload systems.…”

“…This can be realized through the use of hierarchical architectures for decentralized planning, reasoning, learning, and perception that address scalability and information management in the presence of uncertainties. Hierarchical approaches are pervasive in both the machine learning and control fields for dealing with complexity and high dimensionality (e.g., hierarchical task networks (HTNs) [11], hierarchical tree or lattice networks employed in Sequential Game Theory [12], and singular perturbation theory [13], [14]). They are also especially well-suited for aerial robots due to the inherent diversity of time scales in the system.…”

UAV attitude estimation based on the dual filtering methods

“…In the future, full self-driving car will be accepted as a common driving pattern. (Paull et al, 2014;Skulstad et al, 2015;Hakan et al, 2017), flapping wing (Roll et al, 2015;Paranjape et al, 2013;Hoang et al, 2015) and rotor type (Driessens and Pounds, 2015;Miao and Li, 2015;Deepak and Pritpal, 2016). A quad-rotor aircraft is a kind of low-cost rotor-type miniature UAV with a simple mechanical structure but requires automatic controllers and navigation systems to International Journal of Intelligent provide complete stability while flying and performing maneuvers.…”

Motion primitives and 3D path planning for fast flight through a forest

“…A similar roll-yaw control problem was solved in Paranjape et al (2013a), where wing articulation provided a primarily yaw-based control action. The design of innerloop controllers which actuate the rudder and the elevator for controlling m and a has been addressed for an experimental aircraft in Section 6.1 and follows a similar approach as in Paranjape et al (2013a). We note here that the control law for the rudder deflection d r is of the form r c = r c (m c , V ), a known feed-forward mapping,…”