25 citations · 65 across the 8 of their papers we have counts for
10 papers
Multi-Agent Planning with Spatio-Temporal and Topological Constraints using STL-GO
Sheryl Paul, Vidisha Kudalkar, Anand Balakrishnan +3
Multi-agent planning problems arise in a variety of engineering applications, such as multi-robot wildfire fighting and unmanned aerial inspection in factories. A particular challe…
An Algebraic Framework for Quantitative Semantics of Spatio-Temporal Logic with Graph Operators
Sheryl Paul, Vidisha Kudalkar, Anand Balakrishnan +3
Spatio-Temporal Logic with Graph Operators (STL-GO) extends Signal Temporal Logic (STL) to multi-agent systems via graph operators that count neighboring agents satisfying a proper…
Monitoring Spatially Distributed Cyber-Physical Systems with Alternating Finite Automata
Anand Balakrishnan, Sheryl Paul, Simone Silvetti +2
Modern cyber-physical systems (CPS) can consist of various networked components and agents interacting and communicating with each other. In the context of spatially distributed CP…
Multi-agent Path Finding for Timed Tasks using Evolutionary Games
Sheryl Paul, Anand Balakrishnan, Xin Qin +1
Autonomous multi-agent systems such as hospital robots and package delivery drones often operate in highly uncertain environments and are expected to achieve complex temporal task…
Motion Planning for Automata-based Objectives using Efficient Gradient-based Methods
Anand Balakrishnan, Merve Atasever, Jyotirmoy V. Deshmukh
In recent years, there has been increasing interest in using formal methods-based techniques to safely achieve temporal tasks, such as timed sequence of goals, or patrolling object…
Model-Free Reinforcement Learning for Symbolic Automata-encoded Objectives
Anand Balakrishnan, Stefan Jakšić, Edgar A. Aguilar +2
Reinforcement learning (RL) is a popular approach for robotic path planning in uncertain environments. However, the control policies trained for an RL agent crucially depend on use…
PerceMon: Online Monitoring for Perception Systems
Anand Balakrishnan, Jyotirmoy Deshmukh, Bardh Hoxha +2
Perception algorithms in autonomous vehicles are vital for the vehicle to understand the semantics of its surroundings, including detection and tracking of objects in the environme…
Model-based Reinforcement Learning from Signal Temporal Logic Specifications
Parv Kapoor, Anand Balakrishnan, Jyotirmoy V. Deshmukh
Techniques based on Reinforcement Learning (RL) are increasingly being used to design control policies for robotic systems. RL fundamentally relies on state-based reward functions…
Using Logical Specifications of Objectives in Multi-Objective Reinforcement Learning
Kolby Nottingham, Anand Balakrishnan, Jyotirmoy Deshmukh +1
It is notoriously difficult to control the behavior of reinforcement learning agents. Agents often learn to exploit the environment or reward signal and need to be retrained multip…
Augmenting Visual SLAM with Wi-Fi Sensing For Indoor Applications
Zakieh S. Hashemifar, Charuvahan Adhivarahan, Anand Balakrishnan +1
Recent trends have accelerated the development of spatial applications on mobile devices and robots. These include navigation, augmented reality, human-robot interaction, and other…