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Linear Temporal Logic (LTL) is the standard specification language for reactive systems and is successfully applied in industrial settings. However, many shortcomings of LTL have been identified in the literature, among them the limited…

Logic in Computer Science · Computer Science 2019-09-19 Daniel Neider , Alexander Weinert , Martin Zimmermann

Research in robotic planning with temporal logic specifications, such as Linear Temporal Logic (LTL), has relied on single formulas. However, as task complexity increases, LTL formulas become lengthy, making them difficult to interpret and…

Robotics · Computer Science 2025-06-06 Xusheng Luo , Changliu Liu

In this paper, we investigate the problem of planning an optimal infinite path for a single robot to achieve a linear temporal logic (LTL) task with security guarantee. We assume that the external behavior of the robot, specified by an…

Systems and Control · Electrical Eng. & Systems 2020-10-28 Shuo Yang , Xiang Yin , Shaoyuan Li , Majid Zamani

In this paper, we propose a sampling-based motion planning algorithm that finds an infinite path satisfying a Linear Temporal Logic (LTL) formula over a set of properties satisfied by some regions in a given environment. The algorithm has…

Robotics · Computer Science 2013-07-30 Cristian Ioan Vasile , Calin Belta

Legged robots are able to navigate complex terrains by continuously interacting with the environment through careful selection of contact sequences and timings. However, the combinatorial nature behind contact planning hinders the…

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…

Robotics · Computer Science 2015-03-13 Alphan Ulusoy , Stephen L. Smith , Calin Belta

With the advent of large foundation model based planning, there is a dire need to ensure their output aligns with the stakeholder's intent. When these models are deployed in the real world, the need for alignment is magnified due to the…

Robotics · Computer Science 2024-08-13 Parv Kapoor , Sai Vemprala , Ashish Kapoor

In this paper, we develop a Topological Approximate Dynamic Programming (TADP) method for planningin stochastic systems modeled as Markov Decision Processesto maximize the probability of satisfying high-level systemspecifications expressed…

Optimization and Control · Mathematics 2020-08-04 Lening Li , Jie Fu

This paper proposes a novel methodology for trajectory planning in autonomous vehicles (AVs), addressing the complex challenge of negotiating speed bumps within a unified Mixed-Integer Quadratic Programming (MIQP) framework. By leveraging…

This paper presents a novel method of synthesizing a fragment of a timed discrete event system(TDES),introducing a novel linear temporal logic(LTL), called ticked LTL$_f$. The ticked LTL$_f$ is given as an extension to LTL$_f$, where the…

Systems and Control · Electrical Eng. & Systems 2019-12-06 Takuma Kinugawa , Kazumune Hashimoto , Toshimitsu Ushio

We propose a method for efficient training of Q-functions for continuous-state Markov Decision Processes (MDPs) such that the traces of the resulting policies satisfy a given Linear Temporal Logic (LTL) property. LTL, a modal logic, can…

Machine Learning · Computer Science 2019-03-15 Mohammadhosein Hasanbeig , Alessandro Abate , Daniel Kroening

This paper addresses the planning and control problem for nonlinear systems under Signal Temporal Logic (STL) specifications. We first decompose an STL task into finite local tasks. A sampling-based method generates sequences of local…

Systems and Control · Electrical Eng. & Systems 2026-04-28 Zuodong Pan , Xu Fang , Wei Ren

Traditional motion planning approaches for multi-legged locomotion divide the problem into several stages, such as contact search and trajectory generation. However, reasoning about contacts and motions simultaneously is crucial for the…

This paper proposes an optimization-based task and motion planning framework, named "Logic Network Flow", that integrates temporal logic specifications into mixed-integer programs for efficient robot planning. Inspired by the…

Robotics · Computer Science 2025-09-30 Xuan Lin , Jiming Ren , Yandong Luo , Weijun Xie , Ye Zhao

We provide a dynamic programming algorithm for the monitoring of a fragment of Timed Propositional Temporal Logic (TPTL) specifications. This fragment of TPTL, which is more expressive than Metric Temporal Logic, is characterized by…

Logic in Computer Science · Computer Science 2016-12-12 Adel Dokhanchi , Bardh Hoxha , Cumhur Erkan Tuncali , Georgios Fainekos

This paper addresses a multi-robot planning problem in environments with partially unknown semantics. The environment is assumed to have known geometric structure (e.g., walls) and to be occupied by static labeled landmarks with uncertain…

Robotics · Computer Science 2022-01-14 Yiannis Kantaros , Samarth Kalluraya , Qi Jin , George J. Pappas

In this paper, we propose a model-free reinforcement learning method to synthesize control policies for motion planning problems with continuous states and actions. The robot is modelled as a labeled discrete-time Markov decision process…

Artificial Intelligence · Computer Science 2020-10-01 Chuanzheng Wang , Yinan Li , Stephen L. Smith , Jun Liu

We present a new walking foot-placement controller based on 3LP, a 3D model of bipedal walking that is composed of three pendulums to simulate falling, swing and torso dynamics. Taking advantage of linear equations and closed-form solutions…

Robotics · Computer Science 2018-11-12 Salman Faraji , Philippe Muellhaupt , Auke J. Ijspeert

Behavior Trees (BTs) provide designers an intuitive graphical interface to construct long-horizon plans for autonomous systems. To ensure their correctness and safety, rigorous formal models and verification techniques are essential.…

Robotics · Computer Science 2026-04-15 Ryan Matheu , John S. Baras , Calin Belta

This paper addresses the online motion planning problem of mobile robots under complex high-level tasks. The robot motion is modeled as an uncertain Markov Decision Process (MDP) due to limited initial knowledge, while the task is specified…

Robotics · Computer Science 2023-02-13 Yuyang Zhang , Meng Guo