Mohit Srinivasan

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  • Control of Multi-Agent Systems with Finite Time Control Barrier Certificates and Temporal Logic

    In this paper, a method to synthesize controllers using finite time convergence control barrier functions guided by linear temporal logic specifications for continuous time multi-agent dynamical systems is proposed. Finite time convergence to a desired set in the state space is guaranteed under the existence of a suitable finite time convergence control barrier function. In addition, these barrier functions also guarantee forward invariance once the system converges to the desired set. This allows us to formulate a theoretical framework which synthesizes controllers for the multi-agent system. These properties also enable us to solve the reachability problem in continuous time by formulating a theorem on the composition of multiple finite time convergence control barrier functions. This approach is more flexible than existing methods and also allows for a greater set of feasible control laws. Linear temporal logic is used to specify complex task specifications that need to be satisfied by the multi-agent system. With this solution methodology, a control law is synthesized that satisfies the given temporal logic task specification. Robotic experiments are provided which were performed on the Robotarium multi-robot testbed at Georgia Tech.

    08/07/2018 ∙ by Mohit Srinivasan, et al. ∙ 0 share

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  • Control Of Mobile Robots Using Barrier Functions Under Temporal Logic Specifications

    In this paper, we propose a framework for the control of mobile robots subject to temporal logic specifications using barrier functions. Complex task specifications can be conveniently encoded using linear temporal logic (LTL). In particular, we consider a fragment of LTL which encompasses a large class of motion planning specifications for a robotic system. Control barrier functions (CBFs) have recently emerged as a convenient tool to guarantee reachability and safety for a system. In addition, they can be encoded as affine constraints in a quadratic program (QP). In the case of complex system specifications, we show that following QP based methods in existing literature can lead to infeasibility and hence we provide a method of composition of multiple barrier functions in order to mitigate infeasibility. A scheme to prioritize different barrier functions which allows the user to encode the notion of priority based control, is also introduced. We prove that the resulting system trajectory synthesized by the proposed controller satisfies the given specification. Robotic simulation and experimental results are provided in addition to the theoretical framework.

    08/14/2019 ∙ by Mohit Srinivasan, et al. ∙ 0 share

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  • A Sequential Composition Framework for Coordinating Multi-Robot Behaviors

    A number of coordinated behaviors have been proposed for achieving specific tasks for multi-robot systems. However, since most applications require more than one such behavior, one needs to be able to compose together sequences of behaviors while respecting local information flow constraints. Specifically, when the inter-agent communication depends on inter-robot distances, these constraints translate into particular configurations that must be reached in finite time in order for the system to be able to transition between the behaviors. To this end, we develop a framework based on finite-time convergence control barrier functions that drives the robots to the required configurations. In order to demonstrate the proposed framework, we consider a scenario where a team of eight planar robots explore an urban environment in order to localize and rescue a subject. The results are presented in the form of a case study, which is implemented on a multi-agent robotic test-bed.

    07/17/2019 ∙ by Pietro Pierpaoli, et al. ∙ 0 share

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