Results 1  10
of
12
Revising Motion Planning under Linear Temporal Logic Specifications
 in Partially Known Workspaces. IEEE International Conference on Robotics and Automation
, 2013
"... Abstract — In this paper we propose a generic framework for realtime motion planning based on modelchecking and revision. The task specification is given as a Linear Temporal Logic formula over a finite abstraction of the robot motion. A preliminary motion plan is first generated based on the init ..."
Abstract

Cited by 11 (4 self)
 Add to MetaCart
(Show Context)
Abstract — In this paper we propose a generic framework for realtime motion planning based on modelchecking and revision. The task specification is given as a Linear Temporal Logic formula over a finite abstraction of the robot motion. A preliminary motion plan is first generated based on the initial knowledge of the system model. Then realtime information obtained during the runtime is used to update the system model, verify and further revise the motion plan. The implementation and revision of the motion plan are performed in realtime. This framework can be applied to partiallyknown workspaces and workspaces with large uncertainties. Computer simulations are presented to demonstrate the efficiency of the framework. I.
Optimality and robustness in multirobot path planning with temporal logic constraints
 International Journal of Robotics Research
"... Abstract In this paper we present a method for automatic planning of optimal paths for a group of robots that satisfy a common high level mission specification. The motion of each robot is modeled as a weighted transition system, and the mission is given as a Linear Temporal Logic (LTL) formula ove ..."
Abstract

Cited by 7 (0 self)
 Add to MetaCart
(Show Context)
Abstract In this paper we present a method for automatic planning of optimal paths for a group of robots that satisfy a common high level mission specification. The motion of each robot is modeled as a weighted transition system, and the mission is given as a Linear Temporal Logic (LTL) formula over a set of propositions satisfied at the regions of the environment. In addition, an optimizing proposition must repeatedly be satisfied. The goal is to minimize a cost function that captures the maximum time between successive satisfactions of the optimizing proposition while guaranteeing that the formula is satisfied. When the robots can follow a given trajectory exactly, our method computes a set of optimal satisfying paths that minimize the cost function and satisfy the LTL formula. However, if the traveling times of the robots are uncertain, then the robots may not be able to follow a given trajectory exactly, possibly violating the LTL formula during deployment. We handle such cases by leveraging the communication capabilities of the robots to guarantee correctness during deployment and provide bounds on the deviation from the optimal values. We implement and experimentally evaluate our method for various persistent surveillance tasks in a road network environment.
Leastviolating control strategy synthesis with safety rules
 In Proc. of 16th Int. Conf. on Hybrid Systems: Computation and Control (HSCC
, 2013
"... We consider the problem of automatic control strategy synthesis, for discrete models of robotic systems, to fulfill a task that requires reaching a goal state while obeying a given set of safety rules. In this paper, we focus on the case when the said task is not feasible without temporarily violat ..."
Abstract

Cited by 5 (1 self)
 Add to MetaCart
(Show Context)
We consider the problem of automatic control strategy synthesis, for discrete models of robotic systems, to fulfill a task that requires reaching a goal state while obeying a given set of safety rules. In this paper, we focus on the case when the said task is not feasible without temporarily violating some of the rules. We propose an algorithm that synthesizes a motion which violates only lowest priority rules for the shortest amount of time. Although the proposed algorithm can be applied in a variety of control problems, throughout the paper, we motivate this problem with an autonomous car navigating in an urban environment while abiding by the rules of the road, such as “always stay in the right lane ” and “do not enter the sidewalk. ” We evaluate the algorithm on a case study with several illustrative scenarios.
Optimal Multirobot path planning with LTL constraints: guaranteeing correctness through synchronization
 International Symposium on Distributed Autonomous Robotic Systems
, 2012
"... Abstract In this paper, we consider the automated planning of optimal paths for a robotic team satisfying a high level mission specification. Each robot in the team is modeled as a weighted transition system where the weights have associated deviation values that capture the nondeterminism in the ..."
Abstract

Cited by 4 (1 self)
 Add to MetaCart
(Show Context)
Abstract In this paper, we consider the automated planning of optimal paths for a robotic team satisfying a high level mission specification. Each robot in the team is modeled as a weighted transition system where the weights have associated deviation values that capture the nondeterminism in the traveling times of the robot during its deployment. The mission is given as a Linear Temporal Logic (LTL) formula over a set of propositions satisfied at the regions of the environment. Additionally, we have an optimizing proposition capturing some particular task that must be repeatedly completed by the team. The goal is to minimize the maximum time between successive satisfying instances of the optimizing proposition while guaranteeing that the mission is satisfied even under nondeterministic traveling times. Our method relies on the communication capabilities of the robots to guarantee correctness and maintain performance during deployment. After computing a set of optimal satisfying paths for the members of the team, we also compute a set of synchronization sequences for each robot to ensure that the LTL formula is never violated during deployment. We implement and experimentally evaluate our method considering a persistent monitoring task in a road network environment. 1
Multiagent persistent monitoring in stochastic environments with temporal logic constraints
 in 51st IEEE Conf. Decision and Control, 2012
"... AbstractIn this paper, we consider the problem of generating control policies for a team of robots moving in an environment containing elements with probabilistic behaviors. The team is required to achieve an optimal surveillance mission, in which a certain proposition needs to be satisfied infini ..."
Abstract

Cited by 1 (0 self)
 Add to MetaCart
(Show Context)
AbstractIn this paper, we consider the problem of generating control policies for a team of robots moving in an environment containing elements with probabilistic behaviors. The team is required to achieve an optimal surveillance mission, in which a certain proposition needs to be satisfied infinitely often. The goal is to minimize the average time between satisfying instances of the proposition, while ensuring that the mission is accomplished. By modeling the robots as Transition Systems and the environmental elements as Markov Chains, the problem reduces to finding an optimal control policy satisfying a temporal logic specification on a Markov Decision Process. The existing approaches for this problem are computational intensive and therefore not feasible for a large environment or a large number of robots. To address this issue, we propose an approximate dynamic programming framework. Specifically, we choose a set of basis functions to approximate the optimal cost and find the best parameters for these functions based on the leastsquare approximation. We develop an approximate policy iteration algorithm to implement our framework. We provide illustrative case studies and evaluate our method through simulations.
Revision of specification automata under quantitative preferences,” Cornell University Library arXiv.org
, 2014
"... Abstract — We study the problem of revising specifications with preferences for automata based control synthesis problems. In this class of revision problems, the user provides a numerical ranking of the desirability of the subgoals in their specifications. When the specification cannot be satisfied ..."
Abstract

Cited by 1 (0 self)
 Add to MetaCart
(Show Context)
Abstract — We study the problem of revising specifications with preferences for automata based control synthesis problems. In this class of revision problems, the user provides a numerical ranking of the desirability of the subgoals in their specifications. When the specification cannot be satisfied on the system, then our algorithms automatically revise the specification so that the least desirable user goals are removed from the specification. We propose two different versions of the revision problem with preferences. In the first version, the algorithm returns an exact solution while in the second version the algorithm is an approximation algorithm with nonconstant approximation ratio. Finally, we demonstrate the scalability of our algorithms and we experimentally study the approximation ratio of the approximation algorithm on random problem instances. I.
On the Minimal Revision Problem of Specification Automata
, 2014
"... As robots are being integrated into our daily lives, it becomes necessary to provide guarantees on the safe and provably correct operation. Such guarantees can be provided using automata theoretic task and mission planning where the requirements are expressed as temporal logic specifications. Howeve ..."
Abstract
 Add to MetaCart
As robots are being integrated into our daily lives, it becomes necessary to provide guarantees on the safe and provably correct operation. Such guarantees can be provided using automata theoretic task and mission planning where the requirements are expressed as temporal logic specifications. However, in reallife scenarios, it is to be expected that not all user task requirements can be realized by the robot. In such cases, the robot must provide feedback to the user on why it cannot accomplish a given task. Moreover, the robot should indicate what tasks it can accomplish which are as “close ” as possible to the initial user intent. This paper establishes that the latter problem, which is referred to as the minimal specification revision problem, is NP complete. A heuristic algorithm is presented that can compute good approximations to the Minimal Revision Problem (MRP) in polynomial time. The experimental study of the algorithm demonstrates that in most problem instances the heuristic algorithm actually returns the optimal solution. Finally, some cases where the algorithm does not return the optimal solution are presented.
iii TABLE OF CONTENTS
"... Objective of this thesis project is to build a prototype using Linear Temporal Logic specifications for generating a 2D motion plan commanding an iRobot to fulfill the specifications. This thesis project was created for Cyber Physical Systems Lab in Arizona State University. The end product of this ..."
Abstract
 Add to MetaCart
(Show Context)
Objective of this thesis project is to build a prototype using Linear Temporal Logic specifications for generating a 2D motion plan commanding an iRobot to fulfill the specifications. This thesis project was created for Cyber Physical Systems Lab in Arizona State University. The end product of this thesis is creation of a software solution which can be used in the academia and industry for research in cyber physical systems related applications. The major features of the project are: creating a modular system for motion planning, use of Robot Operating System (ROS), use of triangulation for environment decomposition and using stargazer sensor for localization. The project is built on an open source software called ROS which provides an environment where it is very easy to integrate different modules be it software or hardware on a Linux based platform. Use of ROS implies the project or its modules can be adapted quickly for different applications as the need arises. The final software package created and tested takes a data file as its input which contains the LTL specifications, a symbols list used in the LTL and finally the environment polygon data containing real world coordinates for all polygons and also information on neighbors and parents of each polygon. The software package successfully ran the experiment of coverage, reachability with avoidance and sequencing. i To My Wife & Parents ii ACKNOWLEDGMENTS I would like to express my gratitude to Dr. Georgios Fainekos for giving me an opportunity to work on this research topic and providing valuable guidance, inspiration and support. I would like also thank Dr YannHang Lee and Dr. Partha Dasgupta for their
Incremental Samplingbased Algorithm for Minimumviolation Motion Planning
"... Abstract — This paper studies the problem of control strategy synthesis for dynamical systems with differential constraints to fulfill a given reachability goal while satisfying a set of safety rules. Particular attention is devoted to goals that become feasible only if a subset of the safety rules ..."
Abstract
 Add to MetaCart
(Show Context)
Abstract — This paper studies the problem of control strategy synthesis for dynamical systems with differential constraints to fulfill a given reachability goal while satisfying a set of safety rules. Particular attention is devoted to goals that become feasible only if a subset of the safety rules are violated. The proposed algorithm computes a control law, that minimizes the level of unsafety while the desired goal is guaranteed to be reached. This problem is motivated by an autonomous car navigating an urban environment while following rules of the road such as “always travel in right lane ” and “do not change lanes frequently”. Ideas behind sampling based motionplanning algorithms, such as Probabilistic Road Maps (PRMs) and Rapidlyexploring Random Trees (RRTs), are employed to incrementally construct a finite concretization of the dynamics as a durational Kripke structure. In conjunction with this, a weighted finite automaton that captures the safety rules is used in order to find an optimal trajectory that minimizes the violation of safety rules. We prove that the proposed algorithm guarantees asymptotic optimality, i.e., almostsure convergence to optimal solutions. We present results of simulation experiments and an implementation on an autonomous urban mobilityondemand system. I.
Algorithms for Autonomous Urban Navigation with Formal Specifications
, 2014
"... This thesis addresses problems in planning and control of autonomous agents. The central theme of this work is that integration of “lowlevel control synthesis” and “highlevel decision making ” is essential to devise robust algorithms with provable guarantees on performance. We pursue two main di ..."
Abstract
 Add to MetaCart
This thesis addresses problems in planning and control of autonomous agents. The central theme of this work is that integration of “lowlevel control synthesis” and “highlevel decision making ” is essential to devise robust algorithms with provable guarantees on performance. We pursue two main directions here. The first part considers planning and control algorithms that satisfy temporal specifications expressed using formal languages. We focus on task specifications that become feasible only if some of the specifications are violated and compute a control law that minimizes the level of unsafety of the system while guaranteeing that it still satisfies the task specification. Examples in this domain