activity
20192025
collaborators

8 papers

cs.RO2025

GO-VMP: Global Optimization for View Motion Planning in Fruit Mapping

Allen Isaac Jose, Sicong Pan, Tobias Zaenker +3

Automating labor-intensive tasks such as crop monitoring with robots is essential for enhancing production and conserving resources. However, autonomously monitoring horticulture c…

cs.RO2025

Map Space Belief Prediction for Manipulation-Enhanced Mapping

Joao Marcos Correia Marques, Nils Dengler, Tobias Zaenker +4

Searching for objects in cluttered environments requires selecting efficient viewpoints and manipulation actions to remove occlusions and reduce uncertainty in object locations, sh…

cs.RO2024

Context-Based Meta Reinforcement Learning for Robust and Adaptable Peg-in-Hole Assembly Tasks

Ahmed Shokry, Walid Gomaa, Tobias Zaenker +5

Autonomous assembly is an essential capability for industrial and service robots, with Peg-in-Hole (PiH) insertion being one of the core tasks. However, PiH assembly in unknown env…

cs.RO2022

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…

cs.RO2021

Combining Local and Global Viewpoint Planning for Fruit Coverage

Tobias Zaenker, Chris Lehnert, Chris McCool +1

Obtaining 3D sensor data of complete plants or plant parts (e.g., the crop or fruit) is difficult due to their complex structure and a high degree of occlusion. However, especially…

cs.RO2020

Viewpoint Planning for Fruit Size and Position Estimation

Tobias Zaenker, Claus Smitt, Chris McCool +1

Modern agricultural applications require knowledge about the position and size of fruits on plants. However, occlusions from leaves typically make obtaining this information diffic…