Browsing by Author "Tanner, Herbert G."
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Item Data-Driven Abstractions for Robots With Stochastic Dynamics(IEEE Transactions on Robotics, 2021-11-22) Tanner, Herbert G.; Stager, AdamThis article describes the construction of stochastic, data-based discrete abstractions for uncertain random processes continuous in time and space. Motivated by the fact that modeling processes often introduce errors which interfere with the implementation of control strategies, here the abstraction process proceeds in reverse: the methodology does not abstract models; rather it models abstractions. Specifically, it first formalizes a template for a family of stochastic abstractions, and then fits the parameters of that template to match the dynamics of the underlying process and ground the abstraction. The article also shows how the parameter-fitting approach can be implemented based on a probabilistic model validation approach which draws from randomized algorithms, and results in a discrete abstract model which is approximately simulated by the actual process physics, at a desired confidence level. In this way, the models afford the implementation of symbolic control plans with probabilistic guarantees at a desired level of fidelity.Item Development and Testing of an Aerial Radiation Detection System(IEEE Sensors Journal, 2021-12-15) Yadav, Indrajeet; Tanner, Herbert G.This paper reports on the design and implementation of an airborne radiation detection system together with its associated signal processing and decision-making algorithms. This system is envisioned as the building block of an aerial radiation sensor network and it is specifically designed to detect weak radiological signatures in transit. The whole system is developed based on low-cost commercial off the shelf (COTS) components, and through a series of detailed experiments and Monte-Carlo tests, the paper shows how it can be deployed in time-critical application scenarios, where the time allocated to detect the source is limited. Performance metrics for the detection algorithms utilized in the system indicate that the reported technology can offer a significant improvement on the detection speeds compared to alternative techniques utilizing the same hardware resources.Item Editorial: Thought leaders in robotics and AI(Frontiers in Robotics and AI, 2023-08-08) Tanner, Herbert G.The purpose of this short Research Topic is to highlight some directions within the long-term research vision of selected robotics experts. The intention is to spark discussion and debated on these subjects as a means of promoting the importance of the associated technical problems and moving the research further forward. The three papers that comprise this Research Topic are titled, in alphabetical order of their authors: “From the lab to the field with evolutionary field robotics,” by Howard; “Progress and challenges in adaptive robotics,” by Nolfi; and “Towards understanding and synthesis of contact-rich anthropomorphic motions throught interactive cyber-physical human” [platfrom] by Yoshida.Item A Hybrid PAC Reinforcement Learning Algorithm for Human-Robot Interaction(Frontiers in Robotics and AI, 2022-03-09) Zehfroosh, Ashkan; Tanner, Herbert G.This paper offers a new hybrid probably approximately correct (PAC) reinforcement learning (RL) algorithm for Markov decision processes (MDPs) that intelligently maintains favorable features of both model-based and model-free methodologies. The designed algorithm, referred to as the Dyna-Delayed Q-learning (DDQ) algorithm, combines model-free Delayed Q-learning and model-based R-max algorithms while outperforming both in most cases. The paper includes a PAC analysis of the DDQ algorithm and a derivation of its sample complexity. Numerical results are provided to support the claim regarding the new algorithm’s sample efficiency compared to its parents as well as the best known PAC model-free and model-based algorithms in application. A real-world experimental implementation of DDQ in the context of pediatric motor rehabilitation facilitated by infant-robot interaction highlights the potential benefits of the reported method.Item Multi-modal Swarm Coordination via Hopf Bifurcations(Journal of Intelligent and Robotic Systems, 2023-10-04) Baxevani, Kleio; Tanner, Herbert G.This paper outlines a methodology for the construction of vector fields that can enable a multi-robot system moving on the plane to generate multiple dynamical behaviors by adjusting a single scalar parameter. This parameter essentially triggers a Hopf bifurcation in an underlying time-varying dynamical system that steers a robotic swarm. This way, the swarm can exhibit a variety of behaviors that arise from the same set of continuous differential equations. Other approaches to bifurcation-based swarm coordination rely on agent interaction which cannot be realized if the swarm members cannot sense or communicate with one another. The contribution of this paper is to offer an alternative method for steering minimally instrumented multi-robot collectives with a control strategy that can realize a multitude of dynamical behaviors without switching their constituent equations. Through this approach, analytical solutions for the bifurcation parameter are provided, even for more complex cases that are described in the literature, along with the process to apply this theory in a multi-agent setup. The theoretical predictions are confirmed via simulation and experimental results with the latter also demonstrating real-world applicability.Item Navigation Functions with Moving Destinations and Obstacles(Autonomous Robots, 2022) Wei, Cong; Chen, Chuchu; Tanner, Herbert G.Dynamic environments challenge existing robot navigation methods, necessitating either stringent assumptions on workspace variation or sacrificing collision avoidance and convergence guarantees. This paper shows that the navigation function methodology can preserve such guarantees in a dynamic sphere-world with moving obstacles and a time-varying goal, without prior knowledge of environment variation. Assuming bounds on speeds of robot destination and obstacles, and sufficiently higher maximum robot speed, the navigation function gradient can be used produce robot feedback laws that guarantee obstacle avoidance, and theoretical guarantees of bounded tracking errors and eventual convergence to the target in the case where the latter seizes to move. The efficacy of the gradient-based feedback controller derived from the new navigation function construction is demonstrated both in numerical simulations as well as experimentally.Item Non-Smooth Control Barrier Navigation Functions for STL Motion Planning(Frontiers in Robotics and AI, 2022-04-13) Zehfroosh, Ashkan; Tanner, Herbert G.This paper reports on a new approach to Signal Temporal Logic (STL) control synthesis, that 1) utilizes a navigation function as the basis to construct a Control Barrier Function (CBF), and 2) composes navigation function-based barrier functions using nonsmooth mappings to encode Boolean operations between the predicates that those barrier functions encode. Because of these two key features, the reported approach 1) covers a larger fragment of STL compared to existing approaches, 2) alleviates the computational cost associated with evaluation of the control law for the system in existing STL control barrier function methodologies, and 3) simultaneously relaxes some of the conservativeness of smooth combinations of barrier functions as a means of implementing Boolean operators. The paper demonstrates the efficacy of this new approach with three simulation case studies, one aiming at illustrating how complex STL motion planning specification can be realized, the second highlights the less-conservativeness of the approach in comparison to the existing methods, and another that shows how this technology can be brought to bear to push the envelope in the context of human-robot social interaction.Item Resilient Ground Vehicle Autonomous Navigation in GPS-denied Environments(Guidance, Navigation and Control, 2022-11-23) Baxevani, Kleio; Yadav, Indrajeet; Yang, Yulin; Sebok, Michael; Tanner, Herbert G.; Huang, GuoquanCo-design and integration of vehicle navigation and control and state estimation is key for enabling field deployment of mobile robots in GPS-denied cluttered environments, and sensor calibration is critical for successful operation of both subsystems. This paper demonstrates the potential of this co-design approach with field tests of the integration of a reactive receding horizon-based motion planner and controller with an inertial aided multi-sensor calibration scheme. The reported method provides accurate calibration parameters that improve the performance of the state estimator, and enable the motion controller to generate smooth and continuous minimal-jerk trajectories based on local LiDAR data. Numerical simulations in Unity, and real-world experimental results from the field corroborate the claims of efficacy for the reported autonomous navigation computational pipeline.Item Resilient Supervisory Multiagent Systems(IEEE Transactions on Robotics, 2021-09-28) Baxevani, Kleio; Zehfroosh, Ashkan; Tanner, Herbert G.Accidental or deliberate disruption of the coordination function in a multiagent system has been discussed and referred to in the social sciences literature as leader decapitation; this article outlines a methodology for making multiagent networks resilient to this type of failure, enabling a timely restoration of operation normalcy by leveraging machine learning techniques. The approach involves endowing the agents with a cascade of independent learning modules that enable them to discover over time their role in the overall system coordinating strategy, so that they are able to autonomously implement it when central coordination seizes to function. Through these machine learning algorithms, the agents incrementally identify the overall system’s task specification and simultaneously optimize their strategy to serve the common goal.