相关论文: MRHaD: Mixed Reality-based Hand-Drawn Map Editing …
Mobile manipulator robots operating in complex domestic and industrial environments must effectively coordinate their base and arm motions while avoiding obstacles. While current reactive control methods gracefully achieve this…
Mobile robots rely on maps to navigate through an environment. In the absence of any map, the robots must build the map online from partial observations as they move in the environment. Traditional methods build a map using only direct…
Quadruped robots are currently a widespread platform for robotics research, thanks to powerful Reinforcement Learning controllers and the availability of cheap and robust commercial platforms. However, to broaden the adoption of the…
Embodied navigation is a fundamental capability for robotic agents operating. Real-world deployment requires open vocabulary generalization and low training overhead, motivating zero-shot methods rather than task-specific RL training.…
As see-through Mixed Reality Head-Mounted Displays (MRHMDs) proliferate, their usage is gradually shifting from controlled, private settings to spontaneous, public contexts. While location-based augmented reality mobile games such as…
Most human-robot interfaces, such as joysticks and keyboards, require training and constant cognitive effort and provide a limited degree of awareness of the robots state and its environment. Embodied interactions, instead of interfaces,…
Robotic guidance systems have shown promise in supporting blind and visually impaired (BVI) individuals with wayfinding and obstacle avoidance. However, most existing systems assume a clear path and do not support a critical aspect of…
Mixed Reality (MR) has recently shown great success as an intuitive interface for enabling end-users to teach robots. Related works have used MR interfaces to communicate robot intents and beliefs to a co-located human, as well as developed…
Knowledge of a manipulator's workspace is fundamental for a variety of tasks including robot design, grasp planning and robot base placement. Consequently, workspace representations are well studied in robotics. Two important…
Augmented Reality (AR) navigation via Head-Mounted Displays (HMDs), particularly AR glasses, is revolutionizing the driving experience by integrating real-time routing information into the driver's field of view. Despite the potential of AR…
Recently, there has been a significant amount of research conducted on 3D hand reconstruction to use various forms of human-computer interaction. However, 3D hand reconstruction in the wild is challenging due to extreme lack of in-the-wild…
Human-robot interaction through mixed reality (MR) technologies enables novel, intuitive interfaces to control robots in remote operations. Such interfaces facilitate operations in hazardous environments, where human presence is risky, yet…
Prior robot painting and drawing work, such as FRIDA, has focused on decreasing the sim-to-real gap and expanding input modalities for users, but the interaction with these systems generally exists only in the input stages. To support…
Wheeled robot navigation has been widely used in urban environments, but little research has been conducted on its navigation in wild vegetation. External sensors (LiDAR, camera etc.) are often used to construct point cloud map of the…
In this work, we propose the LiDAR Road-Atlas, a compactable and efficient 3D map representation, for autonomous robot or vehicle navigation in general urban environment. The LiDAR Road-Atlas can be generated by an online mapping framework…
Empowering robots to navigate in a socially compliant manner is essential for the acceptance of robots moving in human-inhabited environments. Previously, roboticists have developed geometric navigation systems with decades of empirical…
Mobile robots operating in human-centered environments must generate not only collision-free paths but also trajectories that follow local behavioral conventions. Conventional costmap-based navigation emphasizes geometric feasibility and…
As head-mounted displays (HMDs) with eye-tracking become increasingly accessible, the need for effective gaze-based interfaces in virtual reality (VR) grows. Traditional gaze- or hand-based navigation often limits user precision or impairs…
This paper proposes an end-to-end deep reinforcement learning approach for mobile robot navigation with dynamic obstacles avoidance. Using experience collected in a simulation environment, a convolutional neural network (CNN) is trained to…
Navigating complex indoor environments requires a deep understanding of the space the robotic agent is acting into to correctly inform the navigation process of the agent towards the goal location. In recent learning-based navigation…