Safe, Remote-Access Swarm Robotics Research on the Robotarium

This paper describes the development of the Robotarium -- a remotely accessible, multi-robot research facility. The impetus behind the Robotarium is that multi-robot testbeds constitute an integral and essential part of the multi-agent research cycle, yet they are expensive, complex, and time-consuming to develop, operate, and maintain. These resource constraints, in turn, limit access for large groups of researchers and students, which is what the Robotarium is remedying by providing users with remote access to a state-of-the-art multi-robot test facility. This paper details the design and operation of the Robotarium as well as connects these to the particular considerations one must take when making complex hardware remotely accessible. In particular, safety must be built in already at the design phase without overly constraining which coordinated control programs the users can upload and execute, which calls for minimally invasive safety routines with provable performance guarantees.Comment: 13 pages, 7 figures, 3 code samples, 72 reference

Coordination of Multirobot Systems Under Temporal Constraints

Multirobot systems have great potential to change our lives by increasing efficiency or decreasing costs in many applications, ranging from warehouse logistics to construction. They can also replace humans in dangerous scenarios, for example in a nuclear disaster cleanup mission. However, teleoperating robots in these scenarios would severely limit their capabilities due to communication and reaction delays. Furthermore, ensuring that the overall behavior of the system is safe and correct for a large number of robots is challenging without a principled solution approach. Ideally, multirobot systems should be able to plan and execute autonomously. Moreover, these systems should be robust to certain external factors, such as failing robots and synchronization errors and be able to scale to large numbers, as the effectiveness of particular tasks might depend directly on these criteria. This thesis introduces methods to achieve safe and correct autonomous behavior for multirobot systems. Firstly, we introduce a novel logic family, called counting logics, to describe the high-level behavior of multirobot systems. Counting logics capture constraints that arise naturally in many applications where the identity of the robot is not important for the task to be completed. We further introduce a notion of robust satisfaction to analyze the effects of synchronization errors on the overall behavior and provide complexity analysis for a fragment of this logic. Secondly, we propose an optimization-based algorithm to generate a collection of robot paths to satisfy the specifications given in counting logics. We assume that the robots are perfectly synchronized and use a mixed-integer linear programming formulation to take advantage of the recent advances in this field. We show that this approach is complete under the perfect synchronization assumption. Furthermore, we propose alternative encodings that render more efficient solutions under certain conditions. We also provide numerical results that showcase the scalability of our approach, showing that it scales to hundreds of robots. Thirdly, we relax the perfect synchronization assumption and show how to generate paths that are robust to bounded synchronization errors, without requiring run-time communication. However, the complexity of such an approach is shown to depend on the error bound, which might be limiting. To overcome this issue, we propose a hierarchical method whose complexity does not depend on this bound. We show that, under mild conditions, solutions generated by the hierarchical method can be executed safely, even if such a bound is not known. Finally, we propose a distributed algorithm to execute multirobot paths while avoiding collisions and deadlocks that might occur due to synchronization errors. We recast this problem as a conflict resolution problem and characterize conditions under which existing solutions to the well-known drinking philosophers problem can be used to design control policies that prevents collisions and deadlocks. We further provide improvements to this naive approach to increase the amount of concurrency in the system. We demonstrate the effectiveness of our approach by comparing it to the naive approach and to the state-of-the-art.PHDElectrical Engineering: SystemsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/162921/1/ysahin_1.pd

Distributed Collision-Free Motion Coordination on a Sphere: A Conic Control Barrier Function Approach

This letter studies a distributed collision avoidance control problem for a group of rigid bodies on a sphere. A rigid body network, consisting of multiple rigid bodies constrained to a spherical surface and an interconnection topology, is first formulated. In this formulation, it is shown that motion coordination on a sphere is equivalent to attitude coordination on the 3-dimensional Special Orthogonal group. Then, an angle-based control barrier function that can handle a geodesic distance constraint on a spherical surface is presented. The proposed control barrier function is then extended to a relative motion case and applied to a collision avoidance problem for a rigid body network operating on a sphere. Each rigid body chooses its control input by solving a distributed optimization problem to achieve a nominal distributed motion coordination strategy while satisfying constraints for collision avoidance. The proposed collision-free motion coordination law is validated via simulation

Coordinated Robot Navigation via Hierarchical Clustering

We introduce the use of hierarchical clustering for relaxed, deterministic coordination and control of multiple robots. Traditionally an unsupervised learning method, hierarchical clustering offers a formalism for identifying and representing spatially cohesive and segregated robot groups at different resolutions by relating the continuous space of configurations to the combinatorial space of trees. We formalize and exploit this relation, developing computationally effective reactive algorithms for navigating through the combinatorial space in concert with geometric realizations for a particular choice of hierarchical clustering method. These constructions yield computationally effective vector field planners for both hierarchically invariant as well as transitional navigation in the configuration space. We apply these methods to the centralized coordination and control of $n$ perfectly sensed and actuated Euclidean spheres in a $d$-dimensional ambient space (for arbitrary $n$ and $d$). Given a desired configuration supporting a desired hierarchy, we construct a hybrid controller which is quadratic in $n$ and algebraic in $d$ and prove that its execution brings all but a measure zero set of initial configurations to the desired goal with the guarantee of no collisions along the way.Comment: 29 pages, 13 figures, 8 tables, extended version of a paper in preparation for submission to a journa