Related papers: Kleinkram: Open Robotic Data Management
This paper addresses the problem of efficiently storing and accessing massive data blocks in a large-scale distributed environment, while providing efficient fine-grain access to data subsets. This issue is crucial in the context of…
We present GeoRocket, a software for the management of very large geospatial datasets in the cloud. GeoRocket employs a novel way to handle arbitrarily large datasets by splitting them into chunks that are processed individually. The…
The need for autonomous robot systems in both the service and the industrial domain is larger than ever. In the latter, the transition to small batches or even "batch size 1" in production created a need for robot control system…
Long-term deployment of a fleet of mobile robots requires reliable and secure two-way communication channels between individual robots and remote human operators for supervision and tasking. Existing open-source solutions to this problem…
CleanRL is an open-source library that provides high-quality single-file implementations of Deep Reinforcement Learning algorithms. It provides a simpler yet scalable developing experience by having a straightforward codebase and…
We present an open-source accessory for the NAO robot, which enables to test computationally demanding algorithms in an external platform while preserving robot's autonomy and mobility. The platform has the form of a backpack, which can be…
In this paper, we design algorithms to protect swarm-robotics applications against sensor denial-of-service (DoS) attacks on robots. We focus on applications requiring the robots to jointly select actions, e.g., which trajectory to follow,…
This paper presents an open-source, lightweight, yet comprehensive software framework, named RPC, which integrates physics-based simulators, planning and control libraries, debugging tools, and a user-friendly operator interface. RPC…
Distributed LiDAR SLAM is crucial for achieving efficient robot autonomy and improving the scalability of mapping. However, two issues need to be considered when applying it in field environments: one is resource limitation, and the other…
Robotic systems are more connected, networked, and distributed than ever. New architectures that comply with the \textit{de facto} robotics middleware standard, ROS\,2, have recently emerged to fill the gap in terms of hybrid systems…
Autonomous exploration in unknown environments remains a fundamental challenge in robotics, particularly for applications such as search and rescue, industrial inspection, and planetary exploration. Multi-robot active SLAM presents a…
We present LiHRA, a novel dataset designed to facilitate the development of automated, learning-based, or classical risk monitoring (RM) methods for Human-Robot Interaction (HRI) scenarios. The growing prevalence of collaborative robots in…
Currently, mobile robots are developing rapidly and are finding numerous applications in the industry. However, several problems remain related to their practical use, such as the need for expensive hardware and high power consumption…
Magnetic navigation systems, including magnetic tracking systems and magnetic actuation systems, have shown great potential for occlusion-free localization and remote control of intracorporeal medical devices and robots in minimally…
The Industry 4.0 paradigm emphasizes the crucial benefits that collaborative robots, i.e., robots able to work alongside and together with humans, could bring to the whole production process. In this context, an enabling technology yet…
In recent years, imitation learning from large-scale human demonstrations has emerged as a promising paradigm for training robot policies. However, the burden of collecting large quantities of human demonstrations is significant in terms of…
From both an educational and research point of view, experiments on hardware are a key aspect of robotics and control. In the last decade, many open-source hardware and software frameworks for wheeled robots have been presented, mainly in…
Human-Robot Teams offer the flexibility needed for partial automation in small and medium-sized enterprises (SMEs). They will thus be an integral part of Factories of the Future. Our research targets a particularly flexible teaming mode,…
Compared to conventional decomposition methods that use ellipses or polygons to represent free space, starshaped representation can better capture the natural distribution of sensor data, thereby exploiting a larger portion of traversable…
Currently, commercially available intelligent transport robots that are capable of carrying up to 90kg of load can cost \$5,000 or even more. This makes real-world experimentation prohibitively expensive and limits the applicability of such…