Core challenges of social robot navigation: A survey

C Mavrogiannis, F Baldini, A Wang, D Zhao… - ACM Transactions on …, 2023 - dl.acm.org
Robot navigation in crowded public spaces is a complex task that requires addressing a
variety of engineering and human factors challenges. These challenges have motivated a …

Embodied communication: How robots and people communicate through physical interaction

A Kalinowska, PM Pilarski… - Annual review of control …, 2023 - annualreviews.org
Early research on physical human–robot interaction (pHRI) has necessarily focused on
device design—the creation of compliant and sensorized hardware, such as exoskeletons …

A review on human–machine trust evaluation: Human-centric and machine-centric perspectives

B Gebru, L Zeleke, D Blankson, M Nabil… - … on Human-Machine …, 2022 - ieeexplore.ieee.org
As complex autonomous systems become increasingly ubiquitous, their deployment and
integration into our daily lives will become a significant endeavor. Human–machine trust …

Plug in the safety chip: Enforcing constraints for llm-driven robot agents

Z Yang, SS Raman, A Shah… - 2024 IEEE International …, 2024 - ieeexplore.ieee.org
Recent advancements in large language models (LLMs) have enabled a new research
domain, LLM agents, for solving robotics and planning tasks by leveraging the world …

Formal certification methods for automated vehicle safety assessment

T Zhao, E Yurtsever, JA Paulson… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Challenges related to automated driving are no longer focused on just the construction of
such automated vehicles (AVs) but also on assuring the safety of operation. Recent …

Learning zero-shot cooperation with humans, assuming humans are biased

C Yu, J Gao, W Liu, B Xu, H Tang, J Yang… - arxiv preprint arxiv …, 2023 - arxiv.org
There is a recent trend of applying multi-agent reinforcement learning (MARL) to train an
agent that can cooperate with humans in a zero-shot fashion without using any human data …

A quality diversity approach to automatically generating human-robot interaction scenarios in shared autonomy

M Fontaine, S Nikolaidis - arxiv preprint arxiv:2012.04283, 2020 - arxiv.org
The growth of scale and complexity of interactions between humans and robots highlights
the need for new computational methods to automatically evaluate novel algorithms and …

On specifying for trustworthiness

DB Abeywickrama, A Bennaceur, G Chance… - Communications of the …, 2023 - dl.acm.org
On Specifying for Trustworthiness Page 1 AUTONOMOUS SYSTEMS (AS) are systems that
involve software applications, machines, and people—that is, systems that can take action with …

Evaluating human–robot interaction algorithms in shared autonomy via quality diversity scenario generation

MC Fontaine, S Nikolaidis - ACM Transactions on Human-Robot …, 2022 - dl.acm.org
The growth of scale and complexity of interactions between humans and robots highlights
the need for new computational methods to automatically evaluate novel algorithms and …

Correct me if i'm wrong: Using non-experts to repair reinforcement learning policies

S Van Waveren, C Pek, J Tumova… - 2022 17th ACM/IEEE …, 2022 - ieeexplore.ieee.org
Reinforcement learning has shown great potential for learning sequential decision-making
tasks. Yet, it is difficult to anticipate all possible real-world scenarios during training, causing …