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Core challenges of social robot navigation: A survey
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 …
variety of engineering and human factors challenges. These challenges have motivated a …
Embodied communication: How robots and people communicate through physical interaction
Early research on physical human–robot interaction (pHRI) has necessarily focused on
device design—the creation of compliant and sensorized hardware, such as exoskeletons …
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
As complex autonomous systems become increasingly ubiquitous, their deployment and
integration into our daily lives will become a significant endeavor. Human–machine trust …
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
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 …
domain, LLM agents, for solving robotics and planning tasks by leveraging the world …
Formal certification methods for automated vehicle safety assessment
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 …
such automated vehicles (AVs) but also on assuring the safety of operation. Recent …
Learning zero-shot cooperation with humans, assuming humans are biased
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 …
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
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 …
the need for new computational methods to automatically evaluate novel algorithms and …
On specifying for trustworthiness
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 …
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
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 …
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
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 …
tasks. Yet, it is difficult to anticipate all possible real-world scenarios during training, causing …