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Goldie Nejat

20 accepted papers

2026

Mobile Robot Navigation Using Hand-Drawn Maps: A Vision Language Model Approach

ICRA 2026poster

Hand-drawn maps can be used to convey navigation instructions between humans and robots in a natural and efficient manner. However, these maps can often contain inaccuracies such as scale distortions and missing landmarks which present challenges for mobile robot navigation. This paper introduces a …

2026

X-Nav: Learning End-To-End Cross-Embodiment Navigation for Mobile Robots

ICRA 2026poster

Existing navigation methods are primarily designed for specific robot embodiments, limiting their generalizability across diverse robot platforms. In this paper, we introduce X-Nav, a novel framework for end-to-end cross-embodiment navigation where a single unified policy can be deployed across vari…

2025

Mobile Robot Navigation Using Hand-Drawn Maps: A Vision Language Model Approach

RA-L 2025

Hand-drawn maps can be used to convey navigation instructions between humans and robots in a natural and efficient manner. However, these maps can often contain inaccuracies such as scale distortions and missing landmarks which present challenges for mobile robot navigation. This paper introduces a

Cited by 11SourceScholar
2025

OLiVia-Nav: An Online Lifelong Vision Language Approach for Mobile Robot Social Navigation

ICRA 2025

Service robots in human-centered environments such as hospitals, office buildings, and long-term care homes need to navigate while adhering to social norms to ensure the safety and comfortability of the people they are sharing the space with. Furthermore, they need to adapt to new social scenarios t

Cited by 20SourceScholar
2024

NavFormer: A Transformer Architecture for Robot Target-Driven Navigation in Unknown and Dynamic Environments

RA-L 2024

In unknown cluttered and dynamic environments such as disaster scenes, mobile robots need to perform target-driven navigation in order to find people or objects of interest, where the only information provided about these targets are images of the individual targets. In this letter, we introduce Nav

Cited by 34SourceScholar
2023

A Deep Learning Human Activity Recognition Framework for Socially Assistive Robots to Support Reablement of Older Adults

ICRA 2023poster

Many older adults prefer to stay in their own homes and age-in-place. However, physical and cognitive limitations in independently completing activities of daily living (ADLs) requires older adults to receive assistive support, often necessitating transitioning to care centers. In this paper, we pre…

Cited by 9SourceScholar
2023

Deep Reinforcement Learning for Decentralized Multi-Robot Exploration With Macro Actions

RA-L 2023

Cooperative multi-robot teams need to be able to explore cluttered and unstructured environments while dealing with communication dropouts that prevent them from exchanging local information to maintain team coordination. Therefore, robots need to consider high-level teammate intentions during actio

Cited by 53SourceScholar
2023

Robots Autonomously Detecting People: A Multimodal Deep Contrastive Learning Method Robust to Intraclass Variations

RA-L 2023

Robotic detection of people in crowded and/or cluttered human-centered environments including hospitals, stores and airports is challenging as people can become occluded by other people or objects, and deform due to clothing or pose variations. There can also be loss of discriminative visual feature

Cited by 17SourceScholar
2021

A Sim-to-Real Pipeline for Deep Reinforcement Learning for Autonomous Robot Navigation in Cluttered Rough Terrain

RA-L 2021

Robots that autonomously navigate real-world 3D cluttered environments need to safely traverse terrain with abrupt changes in surface normals and elevations. In this letter, we present the development of a novel sim-to-real pipeline for a mobile robot to effectively learn how to navigate real-world

Cited by 94SourceScholar
2020

mROBerTO 2.0 - An Autonomous Millirobot With Enhanced Locomotion for Swarm Robotics

RA-L 2020

Numerous millirobots were developed in the past decade for autonomous swarm systems that aim to utilize large numbers of these units in space-constrained environments. However, the size limitation of these robots has often resulted in their reduced computational, sensing, and locomotion capabilities

Cited by 13SourceScholar
2019

Deep Reinforcement Learning Robot for Search and Rescue Applications: Exploration in Unknown Cluttered Environments

RA-L 2019

Rescue robots can be used in urban search and rescue (USAR) applications to perform the important task of exploring unknown cluttered environments. Due to the unpredictable nature of these environments, deep learning techniques can be used to perform these tasks. In this letter, we present the first

Cited by 351SourceScholar
2019

It Would Make Me Happy if You Used My Guess: Comparing Robot Persuasive Strategies in Social Human-Robot Interaction

RA-L 2019

This letter presents an exploratory social human- robot interaction (HRI) study that investigates and compares the persuasive effectiveness of robots attempting to influence a user with different behavior strategies. Ten multimodal persuasive strategies were uniquely designed based on compliance gai

Cited by 27SourceScholar
2019

Robot Cooperative Behavior Learning Using Single-Shot Learning From Demonstration and Parallel Hidden Markov Models

RA-L 2019

For robots to become collaborative assistants, they need to be capable of naturally interacting with users in real environments. They also need to be able to learn new skills from non-expert users. In this letter, we present a novel parallel hidden Markov model (PaHMM) architecture for learning from

Cited by 16SourceScholar
2016

A learning from demonstration system architecture for robots learning social group recreational activities

IROS 2016poster

Group-based recreational activities have shown to have a number of health benefits for people of all ages. The handful of social robots designed to facilitate such activities are currently only able to implement a priori known recreational activities that have been pre-programmed by human experts. O…

Cited by 17SourceScholar
2016

mROBerTO: A modular millirobot for swarm-behavior studies

IROS 2016poster

Millirobots have increasingly become popular over the past several years, especially for swarm-behavior studies, allowing researchers to run experiments with a large number of units in limited workspaces. However, as these robots have become smaller in size, their sensory capabilities and battery li…

Cited by 40SourceScholar