The use of aerial swarms to solve real-world problems has been increasing steadily, accompanied by falling prices and improving performance of communication, sensing, and processing hardware. The commoditization of hardware has reduced unit costs, thereby lowering the barriers to entry to the field of aerial swarm robotics. A key enabling technology for swarms is the family of algorithms that allow the individual members of the swarm to communicate and allocate tasks amongst themselves, plan their trajectories, and coordinate their flight in such a way that the overall objectives of the swarm are achieved efficiently. These algorithms, often organized in a hierarchical fashion, endow the swarm with autonomy at every level, and the role of a human operator can be reduced, in principle, to interactions at a higher level without direct intervention. This technology depends on the clever and innovative application of theoretical tools from control and estimation. This paper reviews the state of the art of these theoretical tools, specifically focusing on how they have been developed for, and applied to, aerial swarms. Aerial swarms differ from swarms of ground-based vehicles in two respects: they operate in a three-dimensional space and the dynamics of individual vehicles adds an extra layer of complexity. We review dynamic modeling and conditions for stability and controllability that are essential in order to achieve cooperative flight and distributed sensing. The main sections of this paper focus on major results covering trajectory generation, task allocation, adversarial control, distributed sensing, monitoring, and mapping. Wherever possible, we indicate how the physics and subsystem technologies of aerial robots are brought to bear on these individual areas.

/pdf/a-survey-on-aerial-swarm-robotics-htbvw7nqj5.pdf

A Survey on Aerial Swarm Robotics

This paper addresses a flexible micro aerial vehicle (MAV) under spatiotemporally varying disturbances, which is composed of a rigid body and two flexible wings. Based on Hamilton’s principle, a distributed parameter system coupling in bending and twisting, is modeled. Two iterative learning control (ILC) schemes are designed to suppress the vibrations in bending and twisting, reject the distributed disturbances and regulate the displacement of the rigid body to track a prescribed constant trajectory. At the basis of composite energy function, the boundedness and the learning convergence are proved for the closed-loop MAV system. Simulation results are provided to illustrate the effectiveness of the proposed ILC laws.

Iterative Learning Control for a Flapping Wing Micro Aerial Vehicle Under Distributed Disturbances

In this brief, the control problem for flexible wings of a robotic aircraft is addressed by using boundary control schemes Inspired by birds and bats, the wing with flexibility and articulation is modeled as a distributed parameter system described by hybrid partial differential equations and ordinary differential equations Boundary control for both wing twist and bending is proposed on the original coupled dynamics, and bounded stability is proved by introducing a proper Lyapunov function The effectiveness of the proposed control is verified by simulations

Control Design for Nonlinear Flexible Wings of a Robotic Aircraft

Bats have long captured the imaginations of scientists and engineers with their unrivaled agility and maneuvering characteristics, achieved by functionally versatile dynamic wing conformations as well as more than 40 active and passive joints on the wings. Wing flexibility and complex wing kinematics not only bring a unique perspective to research in biology and aerial robotics but also pose substantial technological challenges for robot modeling, design, and control. We have created a fully self-contained, autonomous flying robot that weighs 93 grams, called Bat Bot (B2), to mimic such morphological properties of bat wings. Instead of using a large number of distributed control actuators, we implement highly stretchable silicone-based membrane wings that are controlled at a reduced number of dominant wing joints to best match the morphological characteristics of bat flight. First, the dominant degrees of freedom (DOFs) in the bat flight mechanism are identified and incorporated in B2’s design by means of a series of mechanical constraints. These biologically meaningful DOFs include asynchronous and mediolateral movements of the armwings and dorsoventral movements of the legs. Second, the continuous surface and elastic properties of bat skin under wing morphing are realized by an ultrathin (56 micrometers) membranous skin that covers the skeleton of the morphing wings. We have successfully achieved autonomous flight of B2 using a series of virtual constraints to control the articulated, morphing wings.

A biomimetic robotic platform to study flight specializations of bats

This brief considers the control design problem for a flexible robotic manipulator. Our control strategies are to: 1) move the manipulator to the certain desired angle; 2) suppress the vibration at the neighborhood of the desired angle; and 3) handle the backlash nonlinearity existing in the practical system. Based on the infinite-dimensional dynamic model, a boundary controller with input backlash is designed to achieve the control aims. An output feedback method is adopted to represent a controller to handle the feedback signals that are not able to be measured directly. The effectiveness of the designed controllers and the stability of the system are demonstrated by theoretical analysis, numerical simulations, and physical experiments.

PDE Model-Based Boundary Control Design for a Flexible Robotic Manipulator With Input Backlash

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 lateral-directional 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 proportional-integral-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.

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

Temporal logics are useful for providing concise descriptions of system behavior, and have been successfully used as a language for goal definitions in task planning. Prior works on inferring temporal logic specifications have focused on "summarizing" the input dataset - i.e., finding specifications that are satisfied by all plan traces belonging to the given set. In this paper, we examine the problem of inferring specifications that describe temporal differences between two sets of plan traces. We formalize the concept of providing such contrastive explanations, then present BayesLTL - a Bayesian probabilistic model for inferring contrastive explanations as linear temporal logic (LTL) specifications. We demonstrate the robustness and scalability of our model for inferring accurate specifications from noisy data and across various benchmark planning domains.

/pdf/bayesian-inference-of-linear-temporal-logic-specifications-9uw23mn1jl.pdf

Bayesian Inference of Linear Temporal Logic Specifications for Contrastive Explanations

The generation of near-optimal plans for multi-agent systems with numerical states and temporal actions is computationally challenging. Current off-the-shelf planners can take a very long time before generating a near-optimal solution. In an effort to reduce plan computation time, increase the quality of the resulting plans, and make them more interpretable by humans, we explore collaborative planning techniques that actively involve human users in plan generation. Specifically, we explore a framework in which users provide high-level strategies encoded as soft preferences to guide the low-level search of the planner. Through human subject experimentation, we empirically demonstrate that this approach results in statistically significant improvements to plan quality, without substantially increasing computation time. We also show that the resulting plans achieve greater similarity to those generated by humans with regard to the produced sequences of actions, as compared to plans that do not incorporate userprovided strategies.

Collaborative Planning with Encoding of Users' High-Level Strategies.

We present a joint modeling approach to identify salient discussion points in spoken meetings as well as to label the discourse relations between speaker turns. A variation of our model is also discussed when discourse relations are treated as latent variables. Experimental results on two popular meeting corpora show that our joint model can outperform state-of-the-art approaches for both phrase-based content selection and discourse relation prediction tasks. We also evaluate our model on predicting the consistency among team members’ understanding of their group decisions. Classifiers trained with features constructed from our model achieve significant better predictive performance than the state-of-the-art.

/pdf/joint-modeling-of-content-and-discourse-relations-in-124my9il8p.pdf

Joint Modeling of Content and Discourse Relations in Dialogues

This paper presents an experimental demonstration of perching by a micro aerial vehicle (MAV) equipped with articulated wings. A novel feature of the MAV considered in
this paper is that wing dihedral, controlled independently on both wings, is used for yaw stability and control as well as for maintaining the flight path angle. Yaw stability and control are essential for perching in tightly constrained places. The experiments described in this paper were conducted indoors and flight parameters are measured using the VICON motion capture system.

/pdf/experimental-demonstration-of-perching-by-an-articulated-3qfcw9vh24.pdf

Joseph Kim

Papers

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

Bayesian Inference of Linear Temporal Logic Specifications for Contrastive Explanations

Collaborative Planning with Encoding of Users' High-Level Strategies.

Joint Modeling of Content and Discourse Relations in Dialogues

Experimental Demonstration of Perching by an Articulated Wing MAV