2 citations · 2 across the 1 of their papers we have counts for
6 papers
Occlusion Handling by Pushing for Enhanced Fruit Detection
Ege Gursoy, Dana KuliÄ, Andrea Cherubini
In agricultural robotics, effective observation and localization of fruits present challenges due to occlusions caused by other parts of the tree, such as branches and leaves. Thes…
A Probabilistic Model for Skill Acquisition with Switching Latent Feedback Controllers
Juyan Zhang, Dana Kulic, Michael Burke
Manipulation tasks often consist of subtasks, each representing a distinct skill. Mastering these skills is essential for robots, as it enhances their autonomy, efficiency, adaptab…
Consistency Matters: Defining Demonstration Data Quality Metrics in Robot Learning from Demonstration
Maram Sakr, H. F. Machiel Van der Loos, Dana Kulic +1
Learning from Demonstration (LfD) empowers robots to acquire new skills through human demonstrations, making it feasible for everyday users to teach robots. However, the success of…
Robots Have Been Seen and Not Heard: Effects of Consequential Sounds on Human-Perception of Robots
Aimee Allen, Tom Drummond, Dana KuliÄ
Robots make compulsory machine sounds, known as `consequential sounds', as they move and operate. As robots become more prevalent in workplaces, homes and public spaces, understand…
Sound Judgment: Properties of Consequential Sounds Affecting Human-Perception of Robots
Aimee Allen, Tom Drummond, Dana KuliÄ
Positive human-perception of robots is critical to achieving sustained use of robots in shared environments. One key factor affecting human-perception of robots are their sounds, e…
Demonstration Based Explainable AI for Learning from Demonstration Methods
Morris Gu, Elizabeth Croft, Dana Kulic
Learning from Demonstration (LfD) is a powerful type of machine learning that can allow novices to teach and program robots to complete various tasks. However, the learning process…