9 accepted papers
Pushing is an essential motor skill involved in several manipulation tasks, and has been an important research topic in robotics. Recent works have shown that Deep Q-Networks (DQNs) can learn pushing policies (when, where to push, and how) to solve manipulation tasks, potentially in synergy with oth…
Humans effortlessly solve pushing tasks in everyday life but unlocking these capabilities remains a challenge in robotics because physics models of these tasks are often inaccurate or unattainable. State-of-the-art data-driven approaches learn to compensate for these inaccuracies or replace the appr…
This letter proposes a harvesting robot capable of plucking tea leaves. In order to harvest high-quality tea, the robot is required to pluck the petiole of the leaf without cutting it using blades. To pluck the leaves, it is necessary to reproduce a complicated human hand motion of pulling while rot
The majority of learning from demonstration approaches do not address suboptimal demonstrations or cases when drastic changes in the environment occur after the demonstrations were made. For example, in real teleoperation tasks, the demonstrations provided by the user are often suboptimal due to int…
Robots that can learn over time by interacting with non-technical users must be capable of acquiring new motor skills, incrementally. The problem then is deciding when to teach the robot a new skill or when to rely on the robot generalizing its actions. This decision can be made by the robot if it i
Robot imitation based on observations of the human movement is a challenging problem as the structure of the human demonstrator and the robot learner are usually different. A movement that can be demonstrated well by a human may not be kinematically feasible for robot reproduction. A common approach
Movement primitives are concise movement representations that can be learned from human demonstrations, support generalization to novel situations and modulate the speed of execution of movements. The speed modulation mechanisms proposed so far are limited though, allowing only for uniform speed mod…
Learning motor skills from multiple demonstrations presents a number of challenges. One of those challenges is the occurrence of occlusions and lack of sensor coverage, which may corrupt part of the recorded data. Another issue is the variability in speed of execution of the demonstrations, which ma…
Robots that interact with humans must learn to not only adapt to different human partners but also to new interactions. Such a form of learning can be achieved by demonstrations and imitation. A recently introduced method to learn interactions from demonstrations is the framework of Interaction Prim…