In this paper, we present a method utilizing redundant manipulator analogs for formation control of underactuated autonomous surface vessels (ASVs) with realistic turning constraints and dynamics. The method used relies on casting the swarm as a single entity and utilizing redundant manipulator techniques to guarantee task-level formation control as well as obstacle avoidance and secondary tasks such as mean position control. The method presented differs from other approaches in that the units herein represent a larger class of ASVs with realistic limitations on vessel motions and that the exact position of each of the units on the formation profile is not specified.

In this paper, we present a method utilizing manipulability concepts and redundant manipulator analogs for swarm manipulation of a rigid object in the plane using autonomous surface vessels. The key concepts involve maximizing some metric defined in relation to a manipulability ellipsoid, which represents the mapping between applied thrust and configuration space accelerations for the object. By casting this problem in the framework of redundant manipulation, the proposed method can be carried out in real time, in a possibly changing environment, and can accommodate nonholonomic vehicles and thrust limits on the swarm. The controller includes attachment pose optimization, engagement control as the ASVs approach and attach to the object, and the manipulation control. Simulation studies demonstrate the efficacy of the proposed methods.

In this paper, we present a new abstraction method by which functional capabilities of a swarm of robots can be automatically distributed across a number of objectives. To demonstrate the framework, we provide a simulation study for a swarm of autonomous aerial vehicles performing a reconnaissance mission. The framework developed provides a novel methodology for real-time resource allocation for a wide variety of missions.

This video presents results from an undergraduate research project involving the design and analysis of a lightweight multimode vehicle capable of driving on solid ground, swimming on the surface of the water, climbing up magnetic surfaces and easily transitioning between the three. Locomotion in and out of the water is provided by buoyant paddlewheels on each side of the vehicle. The climbing capability is achieved by the use of strip magnets mounted to each wheel. The physical design of the robot provides efficiency in and out of the water while considering a necessity for stealth, compactness, and minimal weight. This project has been designed with the expectation of adding autonomy to the vehicle.

In this work we consider methods for dynamics-based control of swarms of cooperating differentially-driven mobile robots. The techniques developed enable the use of methods from redundant manipulator control and show a marked improvement over equivalent kinematics-based techniques for both homogeneous and heterogeneous swarms

In this work we consider methods for control of platoons of cooperating nonholonomic vehicles using techniques based on redundant manipulator control. The class of tricycle-like robots is chosen, as it possesses significant limitations and represents a vast class of real vehicles with application beyond the basic differential drive. The method presented accounts for limitations on both steering and speed. The efficacy of the technique is shown through simulation studies.

This paper relates a hybridization of classical control and behavior-based methods for control of cooperating autonomous vehicles performing a search mission. The controller developed inherits the best characteristics of each of the approaches with few of the drawbacks. Simulation studies show the efficacy of the control for a simple mission.

An approach to real-time trajectory generation for platoons of autonomous vehicles is developed from well-known control techniques for redundant robotic manipulators. The partially decentralized structure of this approach permits each vehicle to independently compute its trajectory in real-time using only locally generated information and low-bandwidth feedback generated by a system exogenous to the platoon. Our work is motivated by applications for which communications bandwidth is severely limited, such for platoons of autonomous underwater vehicles. The communication requirements for our trajectory generation approach are independent of the number of vehicles in the platoon, enabling platoons composed of a large number of vehicles to be coordinated despite limited communication bandwidth.

This paper presents the design of a robotic module that is the building block for a magnetically-coupled reconfigurable robot network. The developed module has on-board computation, IR communication and integrated power. The development of this modular network and the associated reconfiguration methodology is motivated by the premise that magnetic latching is much more plausible than physical latching as scale decreases to the micro and nano levels.

Decentralized control of multiple mobile robots for cooperative tasks often requires not only environmental sensing but communication among the robot subsystems. In this work, we develop observer-based methods for characterizing the implicit and explicit communications required for a swarm of robots to successfully achieve classes of control objectives.

This work is an initial step toward combining control theory with computer vision for the case of uncalibrated monocular (or single-camera) three-dimensional manipulation. We investigate an achievable control goal using a novel image measure and derive a sampled-data control system that results in quick convergence of the end-effector trajectory to a depth-invariant velocity subspace in the camera coordinate frame. We also discuss how this uncalibrated behavior can be used to perform online calibration.

Discusses the use of computer vision for real-time state estimation in feedback control systems. To this end, the authors construct a system for visual state estimation of simple state vectors and study the effects of various real-world disturbances on the state estimates. Simulations are performed using a detailed camera model to study the performance of an image plane position estimation algorithm for a single circular feature. Various disturbances, such as lens distortion, noise, defocus, and blurring are simulated and analyzed with respect to this estimation routine and visual state estimation in general.>