activity
20222024
most citedLearning Personalized Human-Aware Robot Navigation Using Virtual Reality Demonstrations from a User Study

16 citations · 19 across the 8 of their papers we have counts for

collaborators

8 papers

cs.RO2024

Sound Matters: Auditory Detectability of Mobile Robots

Subham Agrawal, Marlene Wessels, Jorge de Heuvel +2

Mobile robots are increasingly being used in noisy environments for social purposes, e.g. to provide support in healthcare or public spaces. Since these robots also operate beyond…

cs.RO2024

Demonstration-Enhanced Adaptable Multi-Objective Robot Navigation

Jorge de Heuvel, Tharun Sethuraman, Maren Bennewitz

Preference-aligned robot navigation in human environments is typically achieved through learning-based approaches, utilizing user feedback or demonstrations for personalization. Ho…

cs.RO2024

EnQuery: Ensemble Policies for Diverse Query-Generation in Preference Alignment of Robot Navigation

Jorge de Heuvel, Florian Seiler, Maren Bennewitz

To align mobile robot navigation policies with user preferences through reinforcement learning from human feedback (RLHF), reliable and behavior-diverse user queries are required.…

cs.RO2023★ 1 cited

Spatiotemporal Attention Enhances Lidar-Based Robot Navigation in Dynamic Environments

Jorge de Heuvel, Xiangyu Zeng, Weixian Shi +2

Foresighted robot navigation in dynamic indoor environments with cost-efficient hardware necessitates the use of a lightweight yet dependable controller. So inferring the scene dyn…

cs.RO2023

Subgoal-Driven Navigation in Dynamic Environments Using Attention-Based Deep Reinforcement Learning

Jorge de Heuvel, Weixian Shi, Xiangyu Zeng +1

Collision-free, goal-directed navigation in environments containing unknown static and dynamic obstacles is still a great challenge, especially when manual tuning of navigation pol…

cs.RO2022★ 1 cited

Learning Depth Vision-Based Personalized Robot Navigation From Dynamic Demonstrations in Virtual Reality

Jorge de Heuvel, Nathan Corral, Benedikt Kreis +3

For the best human-robot interaction experience, the robot's navigation policy should take into account personal preferences of the user. In this paper, we present a learning frame…

cs.RO2022★ 1 cited

Handling Sparse Rewards in Reinforcement Learning Using Model Predictive Control

Murad Dawood, Nils Dengler, Jorge de Heuvel +1

Reinforcement learning (RL) has recently proven great success in various domains. Yet, the design of the reward function requires detailed domain expertise and tedious fine-tuning…

cs.RO2022★ 16 cited

Learning Personalized Human-Aware Robot Navigation Using Virtual Reality Demonstrations from a User Study

Jorge de Heuvel, Nathan Corral, Lilli Bruckschen +1

For the most comfortable, human-aware robot navigation, subjective user preferences need to be taken into account. This paper presents a novel reinforcement learning framework to t…