activity
20202026
most citedMulti-robot Mission Planning in Dynamic Semantic Environments

1 citations · 1 across the 6 of their papers we have counts for

collaborators

6 papers

cs.RO2026

Making Infeasible Tasks Feasible: Planning to Reconfigure Disconnected 3D Environments with Movable Objects

Samarth Kalluraya, Yiannis Kantaros

Several planners have been developed to compute dynamically feasible, collision-free robot paths from an initial to a goal configuration. A key assumption in these works is that th…

cs.RO2024

Minimum-Violation Temporal Logic Planning for Heterogeneous Robots under Robot Skill Failures

Samarth Kalluraya, Beichen Zhou, Yiannis Kantaros

In this paper, we consider teams of robots with heterogeneous skills (e.g., sensing and manipulation) tasked with collaborative missions described by Linear Temporal Logic (LTL) fo…

cs.RO2023

Resilient Temporal Logic Planning in the Presence of Robot Failures

Samarth Kalluraya, George J. Pappas, Yiannis Kantaros

Several task and motion planning algorithms have been proposed recently to design paths for mobile robot teams with collaborative high-level missions specified using formal languag…

cs.RO2022

Verified Compositions of Neural Network Controllers for Temporal Logic Control Objectives

Jun Wang, Samarth Kalluraya, Yiannis Kantaros

This paper presents a new approach to design verified compositions of Neural Network (NN) controllers for autonomous systems with tasks captured by Linear Temporal Logic (LTL) form…

cs.RO2022★ 1 cited

Multi-robot Mission Planning in Dynamic Semantic Environments

Samarth Kalluraya, George J. Pappas, Yiannis Kantaros

This paper addresses a new semantic multi-robot planning problem in uncertain and dynamic environments. Particularly, the environment is occupied with non-cooperative, mobile, unce…

cs.RO2020

Perception-Based Temporal Logic Planning in Uncertain Semantic Maps

Yiannis Kantaros, Samarth Kalluraya, Qi Jin +1

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…