23 citations · 67 across the 24 of their papers we have counts for
6 papers · 1 filter
Learning Depth Vision-Based Personalized Robot Navigation From Dynamic Demonstrations in Virtual Reality
Jorge de Heuvel, Nathan Corral, Benedikt Kreis +3
For the best human-robot interaction experience, the robot's navigation policy should take into account personal preferences of the user. In this paper, we present a learning frame…
Handling Sparse Rewards in Reinforcement Learning Using Model Predictive Control
Murad Dawood, Nils Dengler, Jorge de Heuvel +1
Reinforcement learning (RL) has recently proven great success in various domains. Yet, the design of the reward function requires detailed domain expertise and tedious fine-tuning…
NBV-SC: Next Best View Planning based on Shape Completion for Fruit Mapping and Reconstruction
Rohit Menon, Tobias Zaenker, Nils Dengler +1
Active perception for fruit mapping and harvesting is a difficult task since occlusions occur frequently and the location as well as size of fruits change over time. State-of-the-a…
Fruit Mapping with Shape Completion for Autonomous Crop Monitoring
Salih Marangoz, Tobias Zaenker, Rohit Menon +1
Autonomous crop monitoring is a difficult task due to the complex structure of plants. Occlusions from leaves can make it impossible to obtain complete views about all fruits of, e…
Learning Personalized Human-Aware Robot Navigation Using Virtual Reality Demonstrations from a User Study
Jorge de Heuvel, Nathan Corral, Lilli Bruckschen +1
For the most comfortable, human-aware robot navigation, subjective user preferences need to be taken into account. This paper presents a novel reinforcement learning framework to t…
Learning Goal-Oriented Non-Prehensile Pushing in Cluttered Scenes
Nils Dengler, David Großklaus, Maren Bennewitz
Pushing objects through cluttered scenes is a challenging task, especially when the objects to be pushed have initially unknown dynamics and touching other entities has to be avoid…