1 citations · 1 across the 3 of their papers we have counts for
7 papers
STL-Based Synthesis of Feedback Controllers Using Reinforcement Learning
Nikhil Kumar Singh, Indranil Saha
Deep Reinforcement Learning (DRL) has the potential to be used for synthesizing feedback controllers (agents) for various complex systems with unknown dynamics. These systems are e…
DT*: Temporal Logic Path Planning in a Dynamic Environment
Priya Purohit, Indranil Saha
Path planning for a robot is one of the major problems in the area of robotics. When a robot is given a task in the form of a Linear Temporal Logic (LTL) specification such that th…
MT* : Multi-Robot Path Planning for Temporal Logic Specifications
Dhaval Gujarathi, Indranil Saha
We address the path planning problem for a team of robots satisfying a complex high-level mission specification given in the form of an Linear Temporal Logic (LTL) formula. The sta…
Mobile Recharger Path Planning and Recharge Scheduling in a Multi-Robot Environment
Tanmoy Kundu, Indranil Saha
In many multi-robot applications, mobile worker robots are often engaged in performing some tasks repetitively by following pre-computed trajectories. As these robots are battery-p…
Synthesis of Feedback Controller for Nonlinear Control Systems with Optimal Region of Attraction
Ayan Chakraborty, Indranil Saha
We propose a framework for synthesizing a feedback control policy that maximizes the region of attraction (ROA) of a closed-loop nonlinear dynamical system. Our synthesis technique…
SPARCAS: A Decentralized, Truthful Multi-Agent Collision-free Path Finding Mechanism
Sankar Das, Swaprava Nath, Indranil Saha
We propose a decentralized collision-avoidance mechanism for a group of independently controlled robots moving on a shared workspace. Existing algorithms achieve multi-robot collis…