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Deep learning has allowed a paradigm shift in pattern recognition, from using hand-crafted features together with statistical classifiers to using general-purpose learning procedures for learning data-driven representations, features, and…
Several interesting problems in multi-robot systems can be cast in the framework of distributed optimization. Examples include multi-robot task allocation, vehicle routing, target protection, and surveillance. While the theoretical analysis…
Learning-based surface reconstruction based on unsigned distance functions (UDF) has many advantages such as handling open surfaces. We propose SuperUDF, a self-supervised UDF learning which exploits a learned geometry prior for efficient…
Unmanned aerial vehicles (UAVs) are playing an increasingly pivotal role in modern communication networks,offering flexibility and enhanced coverage for a variety of applica-tions. However, UAV networks pose significant challenges due to…
Robotic wheelchairs (RWs) offer significant potential to enhance autonomy and participation for people with mobility impairments, yet many systems have failed to achieve sustained real-world adoption. This narrative literature review…
Even with impressive advances in application-specific models, we still lack knowledge about how to build a model that can learn in a human-like way and do multiple tasks. To learn in a human-like way, we need to provide a diverse experience…
While assistive robots have much potential to help older people with frailty-related needs, there are few in use. There is a gap between what is developed in laboratories and what would be viable in real-world contexts. Through a series of…
Embodied robots which can interact with their environment and neighbours are increasingly being used as a test case to develop Artificial Intelligence. This creates a need for multimodal robot controllers that can operate across different…
Multi-view shape reconstruction has achieved impressive progresses thanks to the latest advances in neural implicit surface rendering. However, existing methods based on signed distance function (SDF) are limited to closed surfaces, failing…
Cybersecurity in robotics is an emerging topic that has gained significant traction. Researchers have demonstrated some of the potentials and effects of cyber attacks on robots lately. This implies safety related adverse consequences…
Quantitatively evaluating and comparing the performance of robotic solutions that are designed to work under a variety of conditions is inherently challenging because they need to be evaluated under numerous precisely repeatable conditions…
In this review we introduce the framework of reality-assisted evolution to summarize a growing trend towards combining model-based and model-free approaches to improve the design of physically embodied soft robots. In silico, data-driven…
In the domain of unmanned vehicles, autonomous robotic swarms promise to deliver increased efficiency and collective autonomy. How these swarms will operate in the future, and what communication requirements and operational boundaries will…
Ensuring safe navigation in complex environments requires accurate real-time traversability assessment and understanding of environmental interactions relative to the robot`s capabilities. Traditional methods, which assume simplified…
Continuum robots (CRs), owing to their compact structure, inherent compliance, and flexible deformation, have been widely applied in various fields. By coordinating multiple CRs to form collaborative continuum robots (CCRs), task…
Being able to explore an environment and understand the location and type of all objects therein is important for indoor robotic platforms that must interact closely with humans. However, it is difficult to evaluate progress in this area…
Learning from Demonstration (LfD) is a popular approach for robots to acquire new skills, but most LfD methods suffer from imperfections in human demonstrations. Prior work typically treats these suboptimalities as random noise. In this…
In this paper, we present an approach for quantifying the propagated uncertainty of robot systems in an online and data-driven manner. Especially in Human-Robot Collaboration, keeping track of the safety compliance during run time is…
Differential drive robots are widely used in various scenarios thanks to their straightforward principle, from household service robots to disaster response field robots. There are several types of driving mechanisms for real-world…
Industrial human-robot collaborative systems must be validated thoroughly with regard to safety. The sooner potential hazards for workers can be exposed, the less costly is the implementation of necessary changes. Due to the complexity of…