Minimum-violation LTL planning with conflicting specifications

Tůmová, Jana; Castro, Luis I. Reyes; Karaman, Sertaç; Rus, Daniela

doi:10.1109/acc.2013.6579837

Cited by 39 publications

(55 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…LTL has become a popular specification language due its expressive power and scalable control synthesis algorithms which can be tailored to specific applications. Moreover, recently, a number of issues relating to specification debugging and revision [8]- [10], on-line plan revision [3] and partial satisfaction of goals [4] are being studied. The latest developments build upon the LTL control synthesis and planning work to provide a complete set of tools for enabling Human-Robot Interaction (HRI).…”

Section: Introductionmentioning

confidence: 99%

A graphical language for LTL motion and mission planning

Srinivas

Kermani

Kim

et al. 2013

2013 IEEE International Conference on Robotics and Biomimetics (ROBIO)

View full text Add to dashboard Cite

Abstract-Linear Temporal Logic (LTL) has recently become a popular high-level specification language for robotic applications. One of the main reasons for the adoption of LTL is that LTL control synthesis algorithms are scalable while providing sufficient expressive power for a range of applications. However, despite the recent progress, one challenge remains. How can a non-expert robot user, who is not a logician, provide mission and motion plans for multiple robots in LTL? In this paper, we propose a graphical specification environment for LTL specifications that utilizes touchscreen technologies. We demonstrate that the graphical interface can express all the properties of interest that have appeared in the literature.

show abstract

Section: Introductionmentioning

confidence: 99%

A graphical language for LTL motion and mission planning

Srinivas

Kermani

Kim

et al. 2013

2013 IEEE International Conference on Robotics and Biomimetics (ROBIO)

View full text Add to dashboard Cite

show abstract

“…Current research such as [151][152][153][154] has investigated similar logic constraints for the robot motion planning problem in deterministic environments. The main idea is to construct suitable approximating discrete structures for logic constraints that represent well the original logical rules in the continuous state space.…”

Section: Logic Constraintsmentioning

confidence: 99%

- Residual Gas and Stochastic Control

Shen¹,

Zhang²,

Jiao³

et al. 2015

Transient Control of Gasoline Engines

View full text Add to dashboard Cite

Controlling dynamical systems in uncertain environments is fundamental and essential in several fields, ranging from robotics, healthcare to economics and finance. In these applications, the required tasks can be modeled as continuous-time, continuous-space stochastic optimal control problems. Moreover, risk management is an important requirement of such problems to guarantee safety during the execution of control policies. However, even in the simplest version, finding closed-form or exact algorithmic solutions for stochastic optimal control problems is comuputationally challenging.The main contribution of this thesis is the development of theoretical foundations, and provably-correct and efficient sampling-based algorithms to solve stochastic optimal control problems in the presence of complex risk constraints.In the first part of the thesis, we consider the mentioned problems without risk constraints. We propose a novel algorithm called the incremental Markov Decision Process (iMDP) to compute incrementally any-time control policies that approximate arbitrarily well an optimal policy in terms of the expected cost. The main idea is to generate a sequence of finite discretizations of the original problem through random sampling of the state space. At each iteration, the discretized problem is a Markov Decision Process that serves as am incrementally refined model of the original problem. We show that the iMDP algorithm guarantees asymptotic optimality while maintaining low computational and space complexity.In the second part of the thesis, we consider risk constraints that are expressed as either bounded trajectory performance or bounded probabilities of failure. For the former, we present the first extended iMDP algorithm to approximate arbitrarily well an optimal feedback policy of the constrained problem. For the latter, we present a martingale approach that diffuses a risk constraint into a martingale to construct time-consistent control policies. The martingale stands for the level of risk tolerance that is contingent on available information over time. By augmenting the system dynamics with the martingale, the original risk-constrained problem is transformed into a stochastic target problem. We present the second extended iMDP algorithm to approximate arbitrarily well an optimal feedback policy of the original problem by sampling in the augmented state space and computing proper boundary values for the reformulated problem. In both cases, sequences of policies returned from the extended algorithms are both probabilistically sound and asymptotically optimal.

show abstract

“…However, they do not consider constraints where the cost or priority changes over time. Tumova et al [34] present an automatic generator for control strategies for a robotic vehicle where constraints are expressed with LTL formulae. The novelty is the possibility of violating a constraint, according to its priority, in order to complete the task (e.g., a road lane should not be crossed, but this is allowed during car parking).…”

Section: Global Constraints and Preferencesmentioning

confidence: 99%

“…A growing set of frameworks in the literature [34,23] proposes to express temporal properties with partial satisfaction using linear temporal logic (LTL). In [23] the authors introduce a method for quantifying the satisfaction of LTL formulae, and propose a planning framework that synthesises robot trajectories with the optimal satisfaction value.…”

Section: Global Constraints and Preferencesmentioning

confidence: 99%

Efficient customisable dynamic motion planning for assistive robots in complex human environments

Colombo

Fontanelli

Legay

et al. 2015

AIS

View full text Add to dashboard Cite

Abstract. People with impaired physical and mental ability often find it challenging to negotiate crowded or unfamiliar environments, leading to a vicious cycle of deteriorating mobility and sociability. To address this issue we present a novel motion planning algorithm that is able to intelligently deal with crowded areas, permanent or temporary anomalies in the environment (e.g., road blocks, wet floors) as well as hard and soft constraints (e.g., "keep a toilet within reach of 10 meters during the journey", "always avoid stairs"). Constraints can be assigned a priority tailored on the user's needs. The planner has been validated by means of simulations and experiments with elderly people within the context of the DALi European project.

show abstract

Minimum-violation LTL planning with conflicting specifications

Cited by 39 publications

References 21 publications

A graphical language for LTL motion and mission planning

A graphical language for LTL motion and mission planning

- Residual Gas and Stochastic Control

Efficient customisable dynamic motion planning for assistive robots in complex human environments

Contact Info

Product

Resources

About