Related papers: A Mini-Review on Mobile Manipulators with Variable…
Planning smooth and energy-efficient motions for wheeled mobile robots is a central task for applications ranging from autonomous driving to service and intralogistic robotics. Over the past decades, a wide variety of motion planners, steer…
The transition to mixed-traffic environments that involve automated vehicles, manually operated vehicles, and vulnerable road users presents new challenges for human-centered automotive research. Despite this, most studies in the domain…
Despite its importance in both industrial and service robotics, mobile manipulation remains a significant challenge as it requires a seamless integration of end-effector trajectory generation with navigation skills as well as reasoning over…
Robots capable of performing manipulation tasks in a broad range of missions in unstructured environments can develop numerous applications to impact and enhance human life. Existing work in robot learning has shown success in applying…
Safety-critical Autonomous Systems require trustworthy and transparent decision-making process to be deployable in the real world. The advancement of Machine Learning introduces high performance but largely through black-box algorithms. We…
Ensuring safe autonomy is crucial for deploying aerial robots in real-world applications. However, safety is a multifaceted challenge that must be addressed from multiple perspectives, including navigation in dynamic environments, operation…
The present cross-disciplinary research explores pedestrian-autonomous vehicle interactions in a safe, virtual environment. We first present contemporary tools in the field and then propose the design and development of a new application…
Most conventional wheeled robots can only move in flat environments and simply divide their planar workspaces into free spaces and obstacles. Deeming obstacles as non-traversable significantly limits wheeled robots' mobility in real-world,…
Mobile Agent is a type of software system which acts "intelligently" on one's behalf with the feature of autonomy, learning ability and most importantly mobility. Now mobile agents are gaining interest in the research community. In this…
This study evaluates pilots' cognitive workload and situational awareness during remote small unmanned aircraft system operations in different wind conditions. To complement the urban air mobility concept that envisions safe, sustainable,…
Continual learning is essential for all real-world applications, as frozen pre-trained models cannot effectively deal with non-stationary data distributions. The purpose of this study is to review the state-of-the-art methods that allow…
In experimental robotics, researchers may face uncertainties in parameters of a robot manipulator that they are working with. This uncertainty may be caused by deviations in the manufacturing process of a manipulator, or changes applied to…
Multiple levels of safety measures are required by multiple interaction modes which collaborative robots need to perform industrial tasks with human co-workers. We develop three independent modules to account for safety in different types…
Control and planning of multi-agent systems is an active and increasingly studied topic of research, with many practical applications such as rescue missions, security, surveillance, and transportation. This thesis addresses the planning…
We present our general-purpose mobile manipulation system consisting of a custom robot platform and key algorithms spanning perception and planning. To extensively test the system in the wild and benchmark its performance, we choose a…
As robots become increasingly prominent in diverse industrial settings, the desire for an accessible and reliable system has correspondingly increased. Yet, the task of meaningfully assessing the feasibility of introducing a new robotic…
We present a fully autonomous real-world RL framework for mobile manipulation that can learn policies without extensive instrumentation or human supervision. This is enabled by 1) task-relevant autonomy, which guides exploration towards…
Autonomous robots often encounter challenging situations where their control policies fail and an expert human operator must briefly intervene, e.g., through teleoperation. In settings where multiple robots act in separate environments, a…
In this survey, we present the current status on robots performing manipulation tasks that require varying contact with the environment, such that the robot must either implicitly or explicitly control the contact force with the environment…
In this context, a major focus of this thesis is on unintentional collisions, where a straight goal is to eliminate injury from users and passerby's via realtime sensing and control systems. A less obvious focus is to combine collision…