Related papers: Semi-Autonomous Planning and Visualization in Virt…
The rapid progress in AI and Robotics may lead to a profound societal transformation, as humans and robots begin to coexist within shared communities, introducing both opportunities and challenges. To explore this future, we present Virtual…
We present a feasibility-driven teleoperation framework designed to generate humanoid multi-contact maneuvers for use in unstructured environments. Our framework is designed for motions with arbitrary contact modes and postures. The…
Recent works have shown that visual pretraining on egocentric datasets using masked autoencoders (MAE) can improve generalization for downstream robotics tasks. However, these approaches pretrain only on 2D images, while many robotics…
This research aims at developing path and motion planning algorithms for a tethered Unmanned Aerial Vehicle (UAV) to visually assist a teleoperated primary robot in unstructured or confined environments. The emerging state of the practice…
Achieving efficient remote teleoperation is particularly challenging in unknown environments, as the teleoperator must rapidly build an understanding of the site's layout. Online 3D mapping is a proven strategy to tackle this challenge, as…
Visual robot navigation within large-scale, semi-structured environments deals with various challenges such as computation intensive path planning algorithms or insufficient knowledge about traversable spaces. Moreover, many…
Self-adaptation approaches usually rely on closed-loop controllers that avoid human intervention from adaptation. While such fully automated approaches have proven successful in many application domains, there are situations where human…
Visual navigation is essential for many applications in robotics, from manipulation, through mobile robotics to automated driving. Deep reinforcement learning (DRL) provides an elegant map-free approach integrating image processing,…
In a human-robot interaction system, the most important thing to consider is the safety of the user. This must be guaranteed in order to implement a reliable system. The main objective of this paper is to generate a safe motion scheme that…
We aim to build complex humanoid agents that integrate perception, motor control, and memory. In this work, we partly factor this problem into low-level motor control from proprioception and high-level coordination of the low-level skills…
In human-robot collaboration (HRC), it is crucial for robot agents to consider humans' knowledge of their surroundings. In reality, humans possess a narrow field of view (FOV), limiting their perception. However, research on HRC often…
We built a spatial hybrid system that combines a personal computer (PC) and virtual reality (VR) for visual sensemaking, addressing limitations in both environments. Although VR offers immense potential for interactive data visualization…
Grounding language to the visual observations of a navigating agent can be performed using off-the-shelf visual-language models pretrained on Internet-scale data (e.g., image captions). While this is useful for matching images to natural…
As collaborative robots enter industrial shop floors, logistics, and manufacturing, rapid and flexible evaluation of human-machine interaction has become more important. The availability of consumer headsets for virtual and augmented…
Virtual Reality (VR) applications often require users to perform actions with two hands when performing tasks and interacting with objects in virtual environments. Although bimanual interactions in VR can resemble real-world interactions --…
Teleoperating a robot arm involves the human operator positioning the robot's end-effector or programming each joint. Whereas humans can control their own arms easily by integrating visual and proprioceptive feedback, it is challenging to…
Researchers and robotic development groups have recently started paying special attention to autonomous mobile robot navigation in indoor environments using vision sensors. The required data is provided for robot navigation and object…
Tool use is essential for enabling robots to perform complex real-world tasks, but learning such skills requires extensive datasets. While teleoperation is widely used, it is slow, delay-sensitive, and poorly suited for dynamic tasks. In…
We propose a new approach for interaction in Virtual Reality (VR) using mobile robots as proxies for haptic feedback. This approach allows VR users to have the experience of sharing and manipulating tangible physical objects with remote…
Virtual Reality, and Extended Reality in general, connect the physical body with the virtual world. Movement of our body translates to interactions with this virtual world. Only by moving our head will we see a different perspective. By…