To perch on or grasp the objective surface using the suction cup-based manipulator, the precise contact control is commonly required Improper contact angle or insufficient contact force may cause failure To enhance the tolerance to flight control insufficiency, a suction cup that comprises an inner soft cup and an outer firm cup to facilitate its engagement without reducing the adhesion stiffness is investigated The soft cup is adaptable to the angular error induced by the multicopter and the resulting adhesion force can draw the firm cup and correct the angular error between the firm cup and the surface These effects increase the engagement rate and reduce the dependence on precise control The outer firm cup is devoted to providing a large adhesion force and a stiff base for subsequent tasks To reduce the air evacuation time in the firm cup, a novel self-sealing structure is designed Based on the combined cup, we build a multifunctional aerial manipulation system which can execute perching or lateral aerial grasping tasks With the proposed prototype, the comparative flight experiments involving perching on a wall under disturbance and grasping an object are conducted The results demonstrate that our proposed suction cup outperforms the conventional cup

Adaptive Aerial Grasping and Perching With Dual Elasticity Combined Suction Cup

An exponential stabilization criterion for switched delayed interval type-2 fuzzy systems under admissible edge-dependent average dwell time mechanism

Coordinated Route Planning of Multiple Fuel-constrained Unmanned Aerial Systems with Recharging on an Unmanned Ground Vehicle for Mission Coverage

A survey of guidance, navigation, and control systems for autonomous multi-rotor small unmanned aerial systems

Design, development and experimental validation of a lightweight dual-arm aerial manipulator with a COG balancing mechanism

Multiple small, low cost, multi-rotor Unmanned Aerial Vehicles (UAVs) are ideal for aerial surveillance over large areas. However, their limited battery capacity restricts them to areas in proximity of stationary recharging depots. One solution is to use an Unmanned Ground Vehicle (UGV) to provide a moving recharging depot. The problem is then to find the time-or energy-optimal paths for the multiple fuel-constrained UAVs to visit a set of mission points while being recharged by stopping at the UGV, whose path also needs to be determined. This is a combinatorial optimization problem that is computationally challenging, but may be solved relatively fast using heuristics. In this paper, we present two-level optimization that involves, (1) finding a UGV path by fixing waypoints using K-means and then formulating and solving a traveling salesman problem (TSP), and (2) finding paths for the multiple UAVs using a vehicle routing problem (VRP) formulation with capacity constraints, time windows, and dropped visits. We used constraint programming to solve these problems in less than a minute on a standard desktop computer for up to 25 mission points and 4 UAVs. Our main observation is that increasing the number of UAVs decreases the mission time and refueling stops, but does not decrease the total distance covered or total time taken.

Cooperative route planning of multiple fuel-constrained Unmanned Aerial Vehicles with recharging on an Unmanned Ground Vehicle

This paper is an initial step toward the realization of an aerial robot that can perform lateral physical work, such as drilling a hole or fastening a screw in a wall. Aerial robots are capable of high maneuverability and can provide access to locations that would be difficult or impossible for ground-based robots to reach. However, to fully utilize this mobility, systems would ideally be able to perform functional work in those locations, requiring the ability to exert lateral forces. To substantially improve a hovering vehicle’s ability to stably deliver large lateral forces, we propose the use of a versatile suction-based gripper that can establish pulling contact on featureless surfaces. Such contact enables access to environmental forces that can be used to further stabilize the vehicle and also increase the lateral force delivered to the surface through a possible secondary mechanism. This paper introduces the concept, describes the design of a new self-sealing suction cup based on a previous design, details the design of a gripper using those cups, and describes the arm and flight vehicle. It then evaluates the cup and gripper performance in several ways, culminating in physical grasping demonstrations using the arm and gripper, including one in the presence of simulated flight noise based on data from preliminary indoor flight experiments.

Toward Lateral Aerial Grasping & Manipulation Using Scalable Suction

This paper presents an adaptive control law for unknown nonlinear switched plants that must follow the trajectory of user-defined linear switched reference models. The effectiveness of the proposed control architecture is proven in two alternative frameworks, that is, analyzing Caratheodory and Filippov solutions of discontinuous differential equations. Numerical and experimental data verify the applicability of the theoretical results to problems of practical interest. The proposed numerical simulation involves the design of a model reference adaptive control law to regulate the roll dynamics of a reconfigurable delta-wing aircraft. The proposed flight tests involve an aerial robot tasked with autonomously mounting a camera of unknown inertial properties to a vertical surface.

Model Reference Adaptive Control of Switched Dynamical Systems with Applications to Aerial Robotics

Heterogeneous vehicles (e.g., unmanned ground vehicle (UGV) and unmanned aerial vehicle (UAV)) are best suited for surveillance application over large areas. UAVs are fast, but fuel limited, while, UGVs have a larger fuel capacity, but are relatively slow. When UAVs are combined with UGVs they can provide larger coverage at a relatively fast speed. The UAV may also be recharged on the UGV as needed. The resulting route optimization problem is computationally complex, but may be solved relatively fast using heuristics. In this paper, we solve for a mission route using a two-level optimization; (1) the UGV route is assigned using heuristics with free parameters, (2) the UAV route is solved using a vehicle routing problem formulation with capacity constraints, time windows, and dropped visits. However, this open-loop two-level optimization may yield non-optimal solutions or fail completely because of poor choice of UGV parameters. Our primary objective is to explore closed loop optimization where the free parameters of the UGV routes are optimized using Bayesian optimization and Genetic algorithms. Our results show that both methods produce good quality solutions, but bayesian optimization is computationally more efficient than genetic algorithm.

James Dotterweich

Papers

Cooperative route planning of multiple fuel-constrained Unmanned Aerial Vehicles with recharging on an Unmanned Ground Vehicle

Toward Lateral Aerial Grasping & Manipulation Using Scalable Suction

Coordinated Route Planning of Multiple Fuel-constrained Unmanned Aerial Systems with Recharging on an Unmanned Ground Vehicle for Mission Coverage

Model Reference Adaptive Control of Switched Dynamical Systems with Applications to Aerial Robotics

Heterogenous vehicle routing: comparing parameter tuning using genetic algorithm and bayesian optimization