← Search

Tobias Zaenker

8 accepted papers

2025

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

IROS 2025

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 environments is still challenging due to uncertainty in task parameters, such as the hole position and orientation, resulti

Cited by 0SourceScholar
2025

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

IROS 2025

Automating labor-intensive tasks such as crop monitoring with robots is essential for enhancing production and conserving resources. However, autonomously monitoring horticulture crops remains challenging due to their complex structures, which often result in fruit occlusions. Existing view planning

Cited by 6SourceScholar
2025

Map Space Belief Prediction for Manipulation-Enhanced Mapping

RSS 2025poster

Searching for objects in cluttered environments requires selecting efficient viewpoints and manipulation actions to remove occlusions and reduce uncertainty in object locations, shapes, and categories. In this work, we address the problem of manipulation-enhanced semantic mapping, where a robot has…

Cited by 2PDFScholar
2023

Graph-Based View Motion Planning for Fruit Detection

IROS 2023poster

Crop monitoring is crucial for maximizing agricultural productivity and efficiency. However, monitoring large and complex structures such as sweet pepper plants presents significant challenges, especially due to frequent occlusions of the fruits. Traditional next-best view planning can lead to unstr…

Cited by 13SourcecodeScholar
2023

NBV-SC: Next Best View Planning Based on Shape Completion for Fruit Mapping and Reconstruction

IROS 2023poster

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-art viewpoint planning approaches utilize computationally expensive ray casting operations to find good viewpoints aiming…

Cited by 26SourceScholar
2022

Deep Reinforcement Learning for Next-Best-View Planning in Agricultural Applications

ICRA 2022poster

Automated agricultural applications, i.e., fruit picking require spatial information about crops and, especially, their fruits. In this paper, we present a novel deep reinforcement learning (DRL) approach to determine the next best view for automatic exploration of 3D environments with a robotic arm…

Cited by 26SourceScholar
2021

PATHoBot: A Robot for Glasshouse Crop Phenotyping and Intervention

ICRA 2021poster

We present PATHoBot an autonomous crop surveying and intervention robot for glasshouse environments. The aim of this platform is to autonomously gather high quality data and also estimate key phenotypic parameters. To achieve this we retro-fit an off-the-shelf pipe-rail trolley with an array of mult…

Cited by 47SourceScholar
2021

Viewpoint Planning for Fruit Size and Position Estimation

IROS 2021poster

Modern agricultural applications require knowledge about the position and size of fruits on plants. However, occlusions from leaves typically make obtaining this information difficult. We present a novel viewpoint planning approach that builds up an octree of plants with labeled regions of interest…

Cited by 46SourcecodeScholar