Recent trends in task and motion planning for robotics: A survey
Autonomous robots are increasingly served in real-world unstructured human environments
with complex long-horizon tasks, such as restaurant serving and office delivery. Task and …
with complex long-horizon tasks, such as restaurant serving and office delivery. Task and …
Synthesis for robots: Guarantees and feedback for robot behavior
Robot control for tasks such as moving around obstacles or gras** objects has advanced
significantly in the last few decades. However, controlling robots to perform complex tasks is …
significantly in the last few decades. However, controlling robots to perform complex tasks is …
[كتاب][B] Formal methods for discrete-time dynamical systems
C Belta, B Yordanov, EA Gol - 2017 - Springer
In control theory, complex models of physical processes, such as systems of differential or
difference equations, are usually checked against simple specifications, such as stability …
difference equations, are usually checked against simple specifications, such as stability …
Control synthesis from linear temporal logic specifications using model-free reinforcement learning
We present a reinforcement learning (RL) frame-work to synthesize a control policy from a
given linear temporal logic (LTL) specification in an unknown stochastic environment that …
given linear temporal logic (LTL) specification in an unknown stochastic environment that …
Reinforcement learning for temporal logic control synthesis with probabilistic satisfaction guarantees
We present a model-free reinforcement learning algorithm to synthesize control policies that
maximize the probability of satisfying high-level control objectives given as Linear Temporal …
maximize the probability of satisfying high-level control objectives given as Linear Temporal …
Modular deep reinforcement learning for continuous motion planning with temporal logic
This letter investigates the motion planning of autonomous dynamical systems modeled by
Markov decision processes (MDP) with unknown transition probabilities over continuous …
Markov decision processes (MDP) with unknown transition probabilities over continuous …
Asynchronous dissipative control for fuzzy Markov jump systems
The problem of asynchronous dissipative control is investigated for Takagi–Sugeno fuzzy
systems with Markov jump in this paper. Hidden Markov model is introduced to represent the …
systems with Markov jump in this paper. Hidden Markov model is introduced to represent the …
Q-learning for robust satisfaction of signal temporal logic specifications
This paper addresses the problem of learning optimal policies for satisfying signal temporal
logic (STL) specifications by agents with unknown stochastic dynamics. The system is …
logic (STL) specifications by agents with unknown stochastic dynamics. The system is …
A learning based approach to control synthesis of markov decision processes for linear temporal logic specifications
We propose to synthesize a control policy for a Markov decision process (MDP) such that the
resulting traces of the MDP satisfy a linear temporal logic (LTL) property. We construct a …
resulting traces of the MDP satisfy a linear temporal logic (LTL) property. We construct a …
Combining neural networks and tree search for task and motion planning in challenging environments
Task and motion planning subject to Linear Temporal Logic (LTL) specifications in complex,
dynamic environments requires efficient exploration of many possible future worlds. Model …
dynamic environments requires efficient exploration of many possible future worlds. Model …