Related papers: Robot-Assisted Navigation for Visually Impaired th…
Manipulating objects with robotic hands is a complicated task. Not only the fingers of the hand, but also the pose of the robot's end effector need to be coordinated. Using human demonstrations of movements is an intuitive and…
Mobile robots are traditionally developed to be reactive and avoid collisions with surrounding humans, often moving in unnatural ways without following social protocols, forcing people to behave very differently from human-human interaction…
Continuum robots are well suited for navigating confined and fragile environments, such as vascular or endoluminal anatomy, where contact with surrounding structures is often unavoidable. While controlled contact can assist motion,…
This paper develops a robotic manipulation planner for human-robot collaborative assembly. Unlike previous methods which study an independent and fully AI-equipped autonomous system, this paper explores the subtask distribution between a…
While there has been remarkable progress recently in the fields of manipulation and locomotion, mobile manipulation remains a long-standing challenge. Compared to locomotion or static manipulation, a mobile system must make a diverse range…
A particular type of assistive robots designed for physical interaction with objects could play an important role assisting with mobility and fall prevention in healthcare facilities. Autonomous mobile manipulation presents a hurdle prior…
The physically impaired commonly have difficulties performing simple routine tasks without relying on other individuals who are not always readily available and thus make them strive for independence. While their impaired abilities can in…
Assistive and Wearable Robotics have the potential to support humans with different types of motor impairments to become independent and fulfil their activities of daily living successfully. The success of these robot systems, however,…
As more robots are being deployed into human environments, a human-aware navigation planner needs to handle multiple contexts that occur in indoor and outdoor environments. In this paper, we propose a tunable human-aware robot navigation…
This paper describes a system whereby a robot detects and track human-meaningful navigational cues as it navigates in an indoor environment. It is intended as the sensor front-end for a mobile robot system that can communicate its…
Low vision involves a range of visual impairments that significantly impact daily activities, particularly navigation in urban environments. Individuals with low vision often develop adaptive strategies to compensate for visual deficits,…
Effective physical human-robot interaction requires systems that are not only adaptable to user preferences but also transparent about their actions. This paper introduces BRIDGE, a system for bidirectional human-robot communication in…
This paper presents algorithms to navigate and avoid obstacles for an in-door autonomous mobile robot. A laser range finder is used to obtain 3D images of the environment. A new algorithm, namely 3D-to-2D image pressure and barriers…
Navigation and obstacle avoidance are some of the hardest tasks for the visually impaired. Recent research projects have proposed technological solutions to tackle this problem. So far most systems fail to provide multidimensional feedback…
Navigational challenges significantly impact the independence and mobility of Individuals with Visual Impairment (IVI). While numerous assistive technologies exist, their adoption remains limited due to usability challenges, financial…
Manipulation planning is the problem of finding a sequence of robot configurations that involves interactions with objects in the scene, e.g., grasping and placing an object, or more general tool-use. To achieve such interactions,…
Humans can robustly follow a visual trajectory defined by a sequence of images (i.e. a video) regardless of substantial changes in the environment or the presence of obstacles. We aim at endowing similar visual navigation capabilities to…
This paper presents Adaptive Whole-body Loco-Manipulation, AdaptManip, a fully autonomous framework for humanoid robots to perform integrated navigation, object lifting, and delivery. Unlike prior imitation learning-based approaches that…
We present a novel human-aware navigation approach, where the robot learns to mimic humans to navigate safely in crowds. The presented model, referred to as DeepMoTIon, is trained with pedestrian surveillance data to predict human velocity…
Group interactions are essential to social functioning, yet effective engagement relies on the ability to recognize and interpret visual cues, making such engagement a significant challenge for blind people. In this paper, we investigate…