@conference {
	title = {Time varying Control set design for UAV Collision Avoidance Using Reachable Tubes},
	author = {Zhou, Yuchen., Raghavan, Aneesh., Baras, John S.},
	year = {2016},
	month = {12/2016},
	abstract = {In this paper, we propose a reachable set based~collision avoidance algorithm for unmanned aerial vehicles (UAVs). UAVs have been deployed for agriculture research and~management, surveillance and sensor coverage for threat detection~and disaster search and rescue operations. It is essential for~the aircraft to have on-board collision avoidance capability to~guarantee safety. Instead of the traditional approach of collision~avoidance between trajectories, we propose a collision avoidance~scheme based on reachable sets and tubes. We then formulate~the problem as a convex optimization problem seeking time~varying control sets for ego aircraft giving predicted intruder~reachable tube. We have applied the approach on a case study~of two quadrotors collision avoidance scenario.},
	address = {Las Vegas, Nevada},
	booktitle = {55th IEEE Conference on Decision and Control },
	pages = {pp. 6857-6862}
}
@conference {
	title = {Optimal Mission Planning under Logical Constraints with Safety Gaurantees: An Application for Robotic CPSs},
	author = {Maity, Dipankar., Zhou, Yuchen., Baras, John S.},
	year = {2016},
	month = {09/2016},
	address = {Garching, Munich},
	booktitle = {International Symposium on Networked Cyber-Physical Systems (NetCPS)}
}
@conference {
	title = {Timed Automata Approach for Motion Planning Using Metric Interval Temporal Logic},
	author = {Zhou, Yuchen., Maity, Dipankar., Baras, John S.},
	year = {2016},
	month = {06/2016},
	abstract = {In this paper, we consider the robot motion (or~task) planning problem under some given bounded time high-level specifications. We use metric interval temporal logic~(MITL), a member of the temporal logic family, to represent~the task specification and then we provide a constructive way to~generate a timed automaton and methods to look for accepting~runs on the automaton to find a feasible motion (or path)~sequence for the robot to complete the task.~},
	address = {Aalborg, DK},
	booktitle = {European Control Conference (ECC16)},
	pages = {pp. 690-695}
}
@conference {
	title = {Reachable Set Approach to Collision Avoidance for UAVs},
	author = {Zhou, Yuchen., Baras, John S.},
	year = {2015},
	month = {12/2015},
	abstract = {In this paper, we propose a reachable set based~collision avoidance algorithm for unmanned aerial vehicles~(UAVs). UAVs have been deployed for agriculture research and~management, surveillance and sensor coverage for threat detection~and disaster search and rescue operations. It is essential for~the aircraft to have on-board collision avoidance capability to~guarantee safety. Instead of the traditional approach of collision~avoidance between trajectories, we propose a collision avoidance~scheme based on reachable sets and tubes. We then formulate~the problem as a convex optimization problem seeking suitable~control constraint sets for participating aircraft. We have~applied the approach on a case study of two quadrotors collision~avoidance scenario.},
	address = {Osaka, Japan},
	booktitle = {54th Conference on Control (CDC 2015)},
	pages = {pp. 5947-5952}
}
@conference {
	title = {Optimal Mission Planner with Timed Temporal Logic Constraints},
	author = {Zhou, Yuchen., Maity, Dipankar., Baras, John S.},
	year = {2015},
	month = {07/2015},
	abstract = {In this paper, we present an optimization-based~method for path planning of a mobile robot subject to time~bounded temporal constraints, in a dynamic environment.~Temporal logic (TL) can address very complex task specification~such as safety, coverage, motion sequencing etc. We use metric temporal logic (MTL) to encode the task specifications with timing constraints.We then translate the MTL formulae into mixed~integer linear constraints and solve the associated optimization~problem using a mixed integer linear program solver. This~approach is different from the automata-based methods which generate a finite abstraction of the environment and dynamics,~and use an automata-theoretic approach to formally generate~a path that satisfies the TL specifications. We have applied~our approach on several case studies in complex dynamical~environments subjected to timed temporal specifications.},
	address = {Linz, Austria},
	booktitle = {European Control Conference (ECC15)},
	pages = {pp. 759-764}
}
@conference {
	title = {Hardware Software Co-design for Automotive CPS using Architecture Analysis and Design Language},
	author = {Zhou, Yuchen., Baras, John S., Wang, Shige.},
	year = {2014},
	month = {12/2014},
	abstract = {Modern cyber-physical system (CPS) has a close relationship between software and physical system. Automotive embedded system is a typical CPS, as physical chips, sensors and actuators are physical components and software embedded within are the cyber components. The current stage of embedded systems is highly complex in architecture design for both software and hardware. It is common in industrial practice that high level control algorithm development and low level code implementation on hardware platforms are developed separately with limited shared information.However, software code and hardware architecture become closely related with the increasing complexity.Correlated requirements and dependencies between hardware end software are emerging problems of industrial practice. We demonstrate in this paper a method to link model based system design with real-time simulations and analysis of the architecture model. This allows hardware software co-design and thus early selection of hardware architecture.},
	address = {Rome, Italy},
	booktitle = {5th Analytic Virtual Integration of Cyber-Physical Systems Workshop (AVICPS 2014)}
}
@conference {
	title = {A Systems Engineering Approach to Collaborative Coordination of UAS in the NAS with Safety Guarantees},
	author = {Moschler, Jacob., Zhou, Yuchen., Baras, John S., Joh, Jungwoo.},
	year = {2014},
	month = {04/2014},
	abstract = {We develop new fundamental methodologies for high performance and provably safe autonomous and collaborative control and operation of autonomous unmanned aerial systems (UAS) in the national airspace (NAS), where both UAS and manned aircraft fly. The proposed framework is model-based, and emphasizes multiple scales in time and space as well as hybrid systems mathematics to capture both the analog and logical components of control functionalities. We develop on-line control laws that allow for multiple UAS agents to reconfigure to different formations with proofs of safety and convergence while navigating in integrated airspace with piloted air vehicles. We demonstrate our results in simulated scenaria with both cooperative and uncooperative air vehicles.},
	address = {Herndon, Virginia},
	booktitle = {Proceedings of the 2014 Integrated Communications Navigation and Surveillance (ICNS) Conference},
	pages = {pp. U1-1 -U1-12}
}
@conference {
	title = {Compositional Analysis of Dynamic Bayesian Networks and Applications to Complex Dynamic System Decomposition},
	author = {Yang, Shahan., Zhou, Yuchen., Baras, John S.},
	year = {2013},
	month = {03/2013},
	abstract = {Dynamic Bayesian networks (DBNs) can be effectively used to model various problems in complex dynamic systems. We perform an empirical investigation on compositional analysis of DBNs using abstraction. In static systems and hidden Markov models, computation of a metric called treewidth induces a tree decomposition that can be used to perform logical or probabilistic inference and max + optimizations in time exponential in treewidth and linear in overall system size. Intuitively, the linear scaling means that very large systems can be analyzed as long as they are sufficiently sparse and well structured. In these simple cases, summary propagation, which uses two operations, summation (projection) and product (composition), suffices to perform the inference or optimization. Here, we begin an extension of this to structured networks of communicating dynamic systems. We define generalizations of projection and composition operators that treat labeled Markov chains as primitive objects. The projection operation, corresponding to summation, is implemented as label deletion followed by exact state reduction for Markov chains, similar to Hopcroft{\textquoteright}s DFA minimization algorithm, with O(n log m) complexity. The composition operation is the product of state machines. We use canonical MDDs, similar to BDDs, to capture logical dependencies symbolically. Combining symbolic representations with Markov chain lumping algorithms is a novel contribution. Using this approach, we have created a tool leveraging model based systems engineering technologies. The communicating Markov chains are specified using UML Statecharts via Papyrus extended using an ANTLR parsed domain specific language (DSL). The tool reduces the number of states in networks of Markov chains by several orders of magnitude. In one example, a network having a product state space of more than 600 million states is reduced to about 500 states. A feature of this technique is that the state space is examined incrementally, meaning that the full state space is never explicitly represented, even as an input to the reduction algorithm. The primary reduction appears to come from symmetry which is surprising because the technique includes no explicit symmetry handling. We note that composition is efficient at least for systems with high symmetry. We describe applications to a hospital intensive care unit (ICU) from a systems engineering perspective.},
	address = {Atlanta, GA},
	booktitle = {Conference on Systems Engineering Research (CSER{\textquoteright}13),},
	pages = {pp. 167-176}
}
@article {
	title = {Reachable Set Approach to Collision Avoidance for UAVs},
	author = {Zhou, Yuchen., Baras, John S.},
	year = {2016},
	month = {07/2016},
	abstract = {In this paper, we propose a reachable set based collision avoidance algorithm for unmanned aerial vehicles (UAVs). UAVs have been deployed for agriculture research and management, surveillance and sensor coverage for threat detection and disaster search and rescue operations. It is essential for the aircraft to have on-board collision avoidance capability to guarantee safety. Instead of the traditional approach of collision avoidance between trajectories, we propose a collision avoidance scheme based on reachable sets and tubes. We then formulate the problem as a convex optimization problem seeking suitable control constraint sets for participating aircraft. We have applied the approach on a case study of two quadrotors and two fix-wing aircraft collision avoidance scenario.},
	journal = {IEEE Transactions on Automatic Control.}
}
@techreport {
	title = {Compositional Analysis of Dynamic Bayesian Networks and Applications to CPS},
	author = {Yang, Shahan., Zhou, Yuchen., Baras, John S.},
	year = {2012},
	month = {12/2012},
	abstract = {Dynamic Bayesian networks (DBNs) can be effectively used to model various problems in complex dynamic systems. We perform an empirical investigation on compositional analysis of DBNs using abstraction. In static systems and hidden Markov models, computation of a metric called treewidth induces a tree decomposition that can be used to perform logical or probabilistic inference and max + optimizations in time exponential in treewidth and linear in overall system size. Intuitively, the linear scaling means that very large systems can be analyzed as long as they are sufficiently sparse and well structured. In these simple cases, summary propagation, which uses two operations, summation (projection) and product (composition), suffices to perform the inference or optimization. Here, we begin an extension of this to structured networks of communicating dynamic systems. We define generalizations of projection and composition operators that treat labeled Markov chains as primitive objects. The projection operation, corresponding to summation, is implemented as label deletion followed by exact state reduction for Markov chains, similar to Hopcroft{\textquoteright}s DFA minimization algorithm, with O(n log m) complexity. The composition operation is the product of state machines. We use canonical MDDs, similar to BDDs, to capture logical dependencies symbolically. Combining symbolic representations with Markov chain lumping algorithms is a novel contribution. Using this approach, we have created a tool leveraging model based systems engineering technologies. The communicating Markov chains are specified using UML Statecharts via Papyrus extended using an ANTLR parsed domain specific language (DSL). The tool reduces the number of states in networks of Markov chains by several orders of magnitude. In one example, a network having a product state space of more than 600 million states is reduced to about 500 states. A feature of this technique is that the state space is examined incrementally, meaning that the full state space is never explicitly represented, even as an input to the reduction algorithm. The primary reduction appears to come from symmetry which is surprising because the technique includes no explicit symmetry handling. We note that composition is efficient at least for systems with high symmetry. We describe applications to a hospital intensive care unit (ICU) from a systems engineering perspective.}
}
