Related papers: Scene Editing as Teleoperation: A Case Study in 6D…
Attaching a robotic manipulator to a flying base allows for significant improvements in the reachability and versatility of manipulation tasks. In order to explore such systems while taking advantage of human capabilities in terms of…
Modern robots can perform a wide range of simple tasks and adapt to diverse scenarios in the well-trained environment. However, deploying pre-trained robot models in real-world user scenarios remains challenging due to their limited…
Assistive teleoperation enhances efficiency via shared control, yet inter-operator variability, stemming from diverse habits and expertise, induces highly heterogeneous trajectory distributions that undermine intent recognition stability.…
Human motion is inherently diverse and semantically rich, while also shaped by the surrounding scene. However, existing motion generation approaches fail to generate semantically diverse motion while simultaneously respecting geometric…
Robotic teleoperation brings great potential for advances within the field of surgery. The ability of a surgeon to reach patient remotely opens exciting opportunities. Early experience with telerobotic surgery has been interesting, but the…
Task-oriented grasping, which involves grasping specific parts of objects based on their functions, is crucial for developing advanced robotic systems capable of performing complex tasks in dynamic environments. In this paper, we propose a…
Human-in-the-loop telerobotic systems (HiLTS) are robotic tools designed to extend and in some circumstances improve the dexterous capabilities of the human operator in virtual and remote environments. Dexterous manipulation, however,…
Adapting robot programmes to changes in the environment is a well-known industry problem, and it is the reason why many tedious tasks are not automated in small and medium-sized enterprises (SMEs). A semantic world model of a robot's…
In this paper, we present the implementation details of a Virtual Reality (VR)-based teleoperation interface for moving a robotic manipulator. We propose an iterative human-in-the-loop design where the user sets the next task-space waypoint…
This paper presents an AI-driven IoT robotic teleoperation system designed for real-time remote manipulation and intelligent visual monitoring, tailored for smart city applications. The architecture integrates a Flutter-based cross-platform…
Teleoperation is a popular solution to remotely support highly automated vehicles through a human remote operator whenever a disengagement of the automated driving system is present. The remote operator wirelessly connects to the vehicle…
We propose an end-to-end Multitask Learning Transformer framework, named MulT, to simultaneously learn multiple high-level vision tasks, including depth estimation, semantic segmentation, reshading, surface normal estimation, 2D keypoint…
We aim to develop an algorithm for robots to manipulate novel objects as tools for completing different task goals. An efficient and informative representation would facilitate the effectiveness and generalization of such algorithms. For…
We present ASSET, a neural architecture for automatically modifying an input high-resolution image according to a user's edits on its semantic segmentation map. Our architecture is based on a transformer with a novel attention mechanism.…
The teleoperation of robots enables remote intervention in distant and dangerous tasks without putting the operator in harm's way. However, remote operation faces fundamental challenges due to limits in communication delays. The proposed…
Lengthy setup processes that require robotics expertise remain a major barrier to deploying robots for tasks involving high product variability and small batch sizes. As a result, collaborative robots, despite their advanced sensing and…
Human-robot teaming (HRT) systems often rely on large-scale datasets of human and robot interactions, especially for close-proximity collaboration tasks such as human-robot handovers. Learning robot manipulation policies from raw,…
Robotic non-destructive disassembly of mating parts remains challenging due to the need for flexible manipulation and the limited visibility of internal structures. This study presents an affordance-guided teleoperation system that enables…
We study the problem of human action recognition using motion capture (MoCap) sequences. Unlike existing techniques that take multiple manual steps to derive standardized skeleton representations as model input, we propose a novel…
Existing bilateral teleoperation platforms still rely on costly rigid six-axis force/torque sensors, tightly coupled leader-follower hardware, and kilohertz control loops. We present a Cartesian bilateral framework built on the…