12 citations · 15 across the 9 of their papers we have counts for
9 papers
Pro-Bench: Prompt-Robust Open-Vocabulary Visual Grounding Across Real-World Heterogeneous Environments
Linus Nwankwo, Muslim Alaran, Christian Rauch +2
Open-vocabulary visual grounding enables robots to localise task-relevant entities from natural-language queries without dependence on predefined perceptual taxonomies. However, ex…
SIL: Symbiotic Interactive Learning for Language-Conditioned Human-Agent Co-Adaptation
Linus Nwankwo, Bjoern Ellensohn, Christian Rauch +1
Today's autonomous agents, largely driven by foundation models (FMs), can understand natural language instructions and solve long-horizon tasks with human-like reasoning. However,…
VLEM: Real-Time 3D Vision-Language Embedding Mapping
Christian Rauch, Björn Ellensohn, Linus Nwankwo +2
Semantic scene understanding in robotics requires representations that are both metric-accurate and queryable via natural language in real-time. While recent Vision-Language Models…
ReLI: Cross-Lingual Language-to-Action Grounding for Human-Robot Interaction
Linus Nwankwo, Bjoern Ellensohn, Ozan Özdenizci +1
Adapting autonomous agents for real-world industrial, domestic, and other daily tasks is currently gaining momentum. However, in global or cross-lingual application contexts, the a…
EnvoDat: A Large-Scale Multisensory Dataset for Robotic Spatial Awareness and Semantic Reasoning in Heterogeneous Environments
Linus Nwankwo, Bjoern Ellensohn, Vedant Dave +5
To ensure the efficiency of robot autonomy under diverse real-world conditions, a high-quality heterogeneous dataset is essential to benchmark the operating algorithms' performance…
Multimodal Human-Autonomous Agents Interaction Using Pre-Trained Language and Visual Foundation Models
Linus Nwankwo, Elmar Rueckert
In this paper, we extended the method proposed in [21] to enable humans to interact naturally with autonomous agents through vocal and textual conversations. Our extended method ex…
The Conversation is the Command: Interacting with Real-World Autonomous Robot Through Natural Language
Linus Nwankwo, Elmar Rueckert
In recent years, autonomous agents have surged in real-world environments such as our homes, offices, and public spaces. However, natural human-robot interaction remains a key chal…
Understanding why SLAM algorithms fail in modern indoor environments
Nwankwo Linus, Elmar Rueckert
Simultaneous localization and mapping (SLAM) algorithms are essential for the autonomous navigation of mobile robots. With the increasing demand for autonomous systems, it is cruci…
ROMR: A ROS-based Open-source Mobile Robot
Nwankwo Linus, Fritze Clemens, Konrad Bartsch +1
Currently, commercially available intelligent transport robots that are capable of carrying up to 90kg of load can cost $5,000 or even more. This makes real-world experimentation…