Related papers: From Raw Data to Shared 3D Semantics: Task-Oriente…
Communication is a core enabler for multi-robot systems (MRS), providing the mechanism through which robots exchange state information, coordinate actions, and satisfy safety constraints. While many MRS autonomy algorithms assume reliable…
Efficient motion intent communication is necessary for safe and collaborative work environments with collocated humans and robots. Humans efficiently communicate their motion intent to other humans through gestures, gaze, and social cues.…
Computation load-sharing across a network of heterogeneous robots is a promising approach to increase robots capabilities and efficiency as a team in extreme environments. However, in such environments, communication links may be…
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…
This paper presents a data-driven decentralized trajectory optimization approach for multi-robot motion planning in dynamic environments. When navigating in a shared space, each robot needs accurate motion predictions of neighboring robots…
In applications such as search and rescue or disaster relief, heterogeneous multi-robot systems (MRS) can provide significant advantages for complex objectives that require a suite of capabilities. However, within these application spaces,…
This paper addresses the problem of optimizing communicated information among heterogeneous, resource-aware robot teams to facilitate their navigation. In such operations, a mobile robot compresses its local map to assist another robot in…
Mobile edge computing (MEC) deployment in a multi-robot cooperation (MRC) system is an effective way to accomplish the tasks in terms of energy consumption and implementation latency. However, the computation and communication resources…
Multiple mobile robots play a significant role in various spatially distributed tasks.In unfamiliar and non-repetitive scenarios, reconstructing the global map is time-inefficient and sometimes unrealistic. Hence, research has focused on…
This paper presents a human-robot trust integrated task allocation and motion planning framework for multi-robot systems (MRS) in performing a set of tasks concurrently. A set of task specifications in parallel are conjuncted with MRS to…
In the context of Human-Robot Collaboration (HRC), it is crucial that the two actors are able to communicate with each other in a natural and efficient manner. The absence of a communication interface is often a cause of undesired…
Collaborative Perception (CP) has shown great potential to achieve more holistic and reliable environmental perception in intelligent unmanned systems (IUSs). However, implementing CP still faces key challenges due to the characteristics of…
Multi-robot rendezvous and exploration are fundamental challenges in the domain of mobile robotic systems. This paper addresses multi-robot rendezvous within an initially unknown environment where communication is only possible after the…
In this work, we present an end-to-end heterogeneous multi-robot system framework where ground robots are able to localize, plan, and navigate in a semantic map created in real time by a high-altitude quadrotor. The ground robots choose and…
Multi-agent neural implicit mapping allows robots to collaboratively capture and reconstruct complex environments with high fidelity. However, existing approaches often rely on synchronous communication, which is impractical in real-world…
We present the design of a mixed reality (MR) telehealth training system that aims to close the gap between in-person and distance training and re-training for medical procedures. Our system uses real-time volumetric capture as a means for…
Autonomous exploration of unknown environments using a team of mobile robots demands distributed perception and planning strategies to enable efficient and scalable performance. Ideally, each robot should update its map and plan its motion…
We are motivated by quantile estimation of algae concentration in lakes and how decentralized multirobot teams can effectively tackle this problem. We find that multirobot teams improve performance in this task over single robots, and…
In this paper, we introduce a multi-robot system that integrates mapping, localization, and task and motion planning (TAMP) enabled by 3D scene graphs to execute complex instructions expressed in natural language. Our system builds a shared…
In this paper, we investigated semantic communication for multi-task processing using an information-theoretic approach. We introduced the concept of a "semantic source", allowing multiple semantic interpretations from a single observation.…