Entrapment/escorting and patrolling missions in multi-robot cluster space control

Abstract-The tasks of entrapping/escorting and patrolling around an autonomous target are presented making use of the multi-robot cluster space control approach. The cluster space control technique promotes simplified specification and monitoring of the motion of mobile multi-robot systems of limited size. Previous work has established the conceptual foundation of this approach and has experimentally verified and validated its use for 2-robot, 3-robot and 4-robot systems, with varying implementations ranging from automated trajectory control to human-in-the-loop piloting. In this publication, we show that the problem of entrapping/escorting/patrolling is trivial to define and manage from a cluster space perspective. Using a 3-robot experimental testbed, results are shown for the given tasks. We also revise the definition of the cluster space framework for a three-robot formation and incorporate a robotlevel obstacle avoidance functionality

Cluster Control of Automated Surface Vessels

This research focuses on the design and control of a fleet of robotic kayaks, and presents experimental data regarding the functionality and performance of the system. One of the key technical challenges in fielding multi-robot systems for real-world applications is the coordination and relative motion control of the individual units. Coordinated formation control of the fleet is implemented through the use of the cluster space control architecture, which is a full-order controller that treats the fleet as a virtual, articulating, kinematic mechanism. The resulting system is capable of autonomous navigation utilizing a centralized controller, currently implemented via a shore-based computer that wirelessly receives ASV data and relays control commands. Using the cluster space control approach, these control commands allow a cluster supervisor to oversee a flexible and mobile formation formed by the ASV cluster. This paper includes an extended appendix which includes MatLab and Simulink code as well as two publications completed in the process of this research

Time-Energy Optimal Cluster Space Motion Planning for Mobile Robot Formations

The motions of a formation of mobile robots along predetermined paths are optimized according to a tunable time-energy cost function using the cluster space approach to multiagent system specification and control. Upon path-parameterizing cluster state variables describing the geometry and pose of a multirobot group, an optimal control problem is formulated that incorporates formation dynamics and state constraints. The optimal trajectory is derived numerically via a gradient search, iterating over the initial value of one costate. A multirobot formation control simulation is then used to demonstrate the effectiveness of the technique. Results indicate that a substantial tradeoff is made between energy expenditure and motion time when considered as minimization criteria in varying proportions, allowing the operator to tailor mission trajectories according to desired levels of each

Dynamic Guarding of Marine Assets Through Cluster Control of Automated Surface Vessel Fleets

There is often a need to mark or patrol marine areas in order to prevent boat traffic from approaching critical regions, such as the location of a high-value vessel, a dive site, or a fragile marine ecosystem. In this paper, we describe the use of a fleet of robotic kayaks that provides such a function: the fleet circumnavigates the critical area until a threatening boat approaches, at which point the fleet establishes a barrier between the ship and the protected area. Coordinated formation control of the fleet is implemented through the use of the cluster-space control architecture, which is a full-order controller that treats the fleet as a virtual, articulating, kinematic mechanism. An application-specific layer interacts with the cluster-space controller in order for an operator to directly specify and monitor guarding-related parameters, such as the spacing between boats. This system has been experimentally verified in the field with a fleet of robotic kayaks. In this paper, we describe the control architecture used to establish the guarding behavior, review the design of the robotic kayaks, and present experimental data regarding the functionality and performance of the system.Fil: Mahacek, Paul. Santa Clara University; Estados UnidosFil: Kitts, Christopher A.. Santa Clara University; Estados UnidosFil: Mas, Ignacio Agustin. Santa Clara University; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Cluster space collision avoidance for mobile two-robot systems,”

Abstract-The cluster space state representation for multirobot systems provides a simple means of specifying and monitoring the geometry and motion characteristics of a cluster of mobile robots. In previous work, this approach has been experimentally verified and validated for controlling the motion of mobile multi-robot systems ranging from land rovers to autonomous boats. In this paper we introduce a compact collision avoidance algorithm that operates at the level of the cluster, leading to coordinated translational and rotational motions that allow obstacles to be avoided while maintaining the relative geometry of the cluster. This paper formulates the potential-field based obstacle avoidance algorithm, describes its integration within the cluster space control architecture, and presents successful experimental results of its application to two simple, diverse multi-robot testbeds

Enclosing a moving target with an optimally rotated and scaled multiagent pattern

We propose a novel control method to enclose a moving target in a two-dimensional setting with a team of agents forming a prescribed geometric pattern. The approach optimises a measure of the overall agent motion costs, via the minimisation of a suitably defined cost function encapsulating the pattern rotation and scaling. We propose two control laws which use global information and make the agents exponentially converge to the prescribed formation with an optimal scale that remains constant, while the team's centroid tracks the target. One control law results in a multiagent pattern that keeps a constant orientation in the workspace; for the other, the pattern rotates with constant speed. These behaviours, whose optimality and steadiness are very relevant for the task addressed, occur independently from the target's velocity. Moreover, the methodology does not require distance measurements, common coordinate references, or communications. We also present formal guarantees of collision avoidance for the proposed approach. Illustrative simulation examples are provided

Cluster Space Gradient Contour Tracking for Mobile Multi-robot Systems

Multi-robot systems have the potential to exceed the performance of many existing robotic systems by taking advantage of the cluster’s redundancy, coverage and flexibility. These unique characteristics of multi-robot systems allow them to perform tasks such as distributed sensing, gradient climbing, and collaborative work more effectively than any single robot system. The purpose of this research was to augment the existing cluster space control technique in order to demonstrate effective gradient-based functionality, specifically, that of tracking gradient contours of specified concentration levels. To do this, we needed first to estimate the direction of the gradient and/or contour based on the real-time measurements made by sensors on the distributed robots, and second, to steer the cluster in the appropriate direction. Successful simulation, characterization, and experimental testing with the developed testbed have validated this approach. The controller enabled the cluster to sense and follow a contour-based trajectory in a parameter field using both a kayak cluster formation and also the land based Pioneer robots. The positive results of this research demonstrate the robustness of the cluster space control while using the contour following technique and suggest the possibility of further expansion with field applications

A Study of Gradient Climbing Technique Using Cluster Space Control of Multi-Robot Systems

The design of the multi-robot system for distributed sensing and gradient climbing focuses on the capability to optimize the performance of tasks simultaneously. The strategy is to utilize the cluster’s redundancy and flexibility to gain and maximize the overall coverage of surveying parameters so as to surpass the performance of any single robot. The collaborative nature of the cluster provides a more efficient and effective platform for collecting data and conducting fieldwork. The purpose of this study is to explore the existing cluster space control technique to show effective gradient-based navigation, particularly that of climbing a gradient in a sensed parameter field to the local maximum. In order to achieve positive results, we need to estimate the gradient direction based on real-time measurements captured by sensors on the distributed robotic network, and then maneuver the cluster to travel in the estimated direction. Verification and characterization of this technique has been performed through both simulation and hardware-in-the-loop experimentation. In these tests, the gradient controller enabled the cluster to sense and climb the gradient in a parameterized field using kayaks in a marine environment and utilizing wheeled robots in a land based system. The successful outcome of these demonstrations proves the value of the cluster space control technique and showcases how it can be used for efficiently locating minimum and maximum features in a parameter field

VEX robotics

The objective of our project was to design and construct a control system for communication between two autonomous robots, of different size and capabilities, in an environment with numerous obstacles and challenges. These challenges, completed autonomously, involved moving over and under barriers along with the obtainment and transportation of spherical objects. Our project was tied to the VEX Robotics competition environment as we tested our robots by competing at the World Championships. Unfortunately, due to time and budget considerations, we had to scale back our sensor subsystem. This led to a simpler control system than originally intended; however, we were successful at the competition, and built robots that were efficient and economic in design. Our results proved that our robot designs were more agile and maneuverable than our opponents when it came to manipulating environment elements, and that our scaled back autonomous programs were still very effective in disrupting opponent robots\u27 routines and strategies

Multi-bot Easy Control Hierarchy

The goal of our project is to create a software architecture that makes it possible to easily control a multi-robot system, as well as seamlessly change control modes during operation. The different control schemes first include the ability to implement on-board and off-board controllers. Second, the commands can specify either actuator level, vehicle level, or fleet level behavior. Finally, motion can be specified by giving a waypoint and time constraint, a velocity and heading, or a throttle and angle. Our code is abstracted so that any type of robot - ranging from ones that use a differential drive set up, to three-wheeled holonomic platforms, to quadcopters - can be added to the system by simply writing drivers that interface with the hardware used and by implementing math packages that do the required calculations. Our team has successfully demonstrated piloting a single robots while switching between waypoint navigation and a joystick controller. In addition, we have demonstrated the synchronized control of two robots using joystick control. Future work includes implementing a more robust cluster control, including off-board functionality, and incorporating our architecture into different types of robots