相关论文: A Hierarchical Architecture for Human-Robot Cooper…

Robots existed as separate entities till now, but the horizons of a symbiotic human-robot partnership are impending. Despite all the recent technical advances in terms of hardware, robots are still not endowed with desirable relational…

Developing robots that can assist humans efficiently, safely, and adaptively is crucial for real-world applications such as healthcare. While previous work often assumes a centralized system for co-optimizing human-robot interactions, we…

We design and develop a new shared Augmented Reality (AR) workspace for Human-Robot Interaction (HRI), which establishes a bi-directional communication between human agents and robots. In a prototype system, the shared AR workspace enables…

Wheelchair-mounted robotic arms (and other assistive robots) should help their users perform everyday tasks. One way robots can provide this assistance is shared autonomy. Within shared autonomy, both the human and robot maintain control…

Physical interactions are inevitable part of human-robot collaboration tasks and rather than exhibiting simple reactive behaviors to human interactions, collaborative robots need to be endowed with intuitive behaviors. This paper proposes a…

We present a visually grounded hierarchical planning algorithm for long-horizon manipulation tasks. Our algorithm offers a joint framework of neuro-symbolic task planning and low-level motion generation conditioned on the specified goal. At…

Human-robot collaboration (HRC) introduces significant safety challenges, particularly in protecting human operators working alongside collaborative robots (cobots). While current ISO standards emphasize risk assessment and hazard…

Human Activity Recognition (HAR) is a pivotal component of robot perception for physical Human Robot Interaction (pHRI) tasks. In construction robotics, it is vital that robots have an accurate and robust perception of worker activities.…

As the use of Augmented Reality (AR) to enhance interactions between human agents and robotic systems in a work environment continues to grow, robots must communicate their intents in informative yet straightforward ways. This improves the…

In the field of Human-Robot Interaction (HRI), many researchers study shared control systems. Shared control is when a person and agent both contribute to the performance of a task in a collaborative way, often by providing control inputs…

In the rapidly evolving landscape of Human-Robot Collaboration (HRC), effective communication between humans and robots is crucial for complex task execution. Traditional request-response systems often lack naturalness and may hinder…

As robot technology advances, collaboration between humans and robots will become more prevalent in industrial tasks. When humans run into issues in such scenarios, a likely future involves relying on artificial agents or robots for aid.…

Semantic SLAM (Simultaneous Localization and Mapping) systems enrich robot maps with structural and semantic information, enabling robots to operate more effectively in complex environments. However, these systems struggle in real-world…

A significant element of human cooperative intelligence lies in our ability to identify opportunities for fruitful collaboration; and conversely to recognise when the task at hand is better pursued alone. Research on flexible cooperation in…

Complex tasks require human collaboration since robots do not have enough dexterity. However, robots are still used as instruments and not as collaborative systems. We are introducing a framework to ensure safety in a human-robot…

Human-robot collaboration (HRC) in structured assembly requires reliable state estimation and adaptive task planning under noisy perception and human interventions. To address these challenges, we introduce a design-grounded human-aware…

There is invariably a trade-off between safety and efficiency for collaborative robots (cobots) in human-robot collaborations. Robots that interact minimally with humans can work with high speed and accuracy but cannot adapt to new tasks or…

The simulation-to-real gap problem and the high computational burden of whole-body Model Predictive Control (whole-body MPC) continue to present challenges in generating a wide variety of movements using whole-body MPC for real humanoid…

Hierarchical agents have the potential to solve sequential decision making tasks with greater sample efficiency than their non-hierarchical counterparts because hierarchical agents can break down tasks into sets of subtasks that only…

Physical human-robot collaboration (pHRC) requires both compliance and safety guarantees since robots coordinate with human actions in a shared workspace. This paper presents a novel fixed-time adaptive neural control methodology for…