Zobrazeno 1 - 10
of 304
pro vyhledávání: '"XU Xiangru"'
The increasing prevalence of neural networks in safety-critical control systems underscores the imperative need for rigorous methods to ensure the reliability and safety of these systems. This work introduces a novel approach employing hybrid zonotop
Externí odkaz:
http://arxiv.org/abs/2310.06921
Autor:
Wang, Yujie, Xu, Xiangru
When the disturbance input matrix is nonlinear, existing disturbance observer design methods rely on the solvability of a partial differential equation or the existence of an output function with a uniformly well-defined disturbance relative degree,
Externí odkaz:
http://arxiv.org/abs/2309.06718
Autor:
Wang, Yujie, Xu, Xiangru
This paper presents a new safe control framework for Euler-Lagrange (EL) systems with limited model information, external disturbances, and measurement uncertainties. The EL system is decomposed into two subsystems called the proxy subsystem and the
Externí odkaz:
http://arxiv.org/abs/2309.04839
Autor:
Zhang, Harry, Caldararu, Stefan, Mahajan, Ishaan, Chatterjee, Shouvik, Hansen, Thomas, Dashora, Abhiraj, Ashokkumar, Sriram, Fang, Luning, Xu, Xiangru, He, Shen, Negrut, Dan
Modeling a robust control system with a precise GPS-based state estimation capability in simulation can be useful in field navigation applications as it allows for testing and validation in a controlled environment. This testing process would enable
Externí odkaz:
http://arxiv.org/abs/2304.09156
The proliferation of neural networks in safety-critical applications necessitates the development of effective methods to ensure their safety. This letter presents a novel approach for computing the exact backward reachable sets of neural feedback sy
Externí odkaz:
http://arxiv.org/abs/2303.10513
Autor:
Wang, Yujie, Xu, Xiangru
This paper presents a novel approach for the safe control design of systems with parametric uncertainties in both drift terms and control-input matrices. The method combines control barrier functions and adaptive laws to generate a safe controller th
Externí odkaz:
http://arxiv.org/abs/2302.08601
Autor:
Elmquist, Asher, Young, Aaron, Hansen, Thomas, Ashokkumar, Sriram, Caldararu, Stefan, Dashora, Abhiraj, Mahajan, Ishaan, Zhang, Harry, Fang, Luning, Shen, He, Xu, Xiangru, Serban, Radu, Negrut, Dan
We discuss a platform that has both software and hardware components, and whose purpose is to support research into characterizing and mitigating the sim-to-real gap in robotics and vehicle autonomy engineering. The software is operating-system indep
Externí odkaz:
http://arxiv.org/abs/2211.04886
Autor:
Zhang, Yuhao, Xu, Xiangru
Hybrid zonotopes generalize constrained zonotopes by introducing additional binary variables and possess some unique properties that make them convenient to represent nonconvex sets. This paper presents novel hybrid zonotope-based methods for the rea
Externí odkaz:
http://arxiv.org/abs/2210.03244
Autor:
Elmquist, Asher, Young, Aaron, Mahajan, Ishaan, Fahey, Kyle, Dashora, Abhiraj, Ashokkumar, Sriram, Caldararu, Stefan, Freire, Victor, Xu, Xiangru, Serban, Radu, Negrut, Dan
We describe a software framework and a hardware platform used in tandem for the design and analysis of robot autonomy algorithms in simulation and reality. The software, which is open source, containerized, and operating system (OS) independent, has
Externí odkaz:
http://arxiv.org/abs/2206.06537
Autor:
Freire, Victor, Xu, Xiangru
The optimal control problem for the kinematic bicycle model is considered where the trajectories are required to satisfy the safety constraints in the continuous-time sense. Based on the differential flatness property of the model, necessary and suff
Externí odkaz:
http://arxiv.org/abs/2204.08980