Kenneth Blomqvist
Papers
4
Total Citations
24
H-Index
3
About
Kenneth Blomqvist is a roboticist advancing the frontier of mobile manipulation and perception in unstructured environments. His research centers on enabling robots to autonomously interact with the physical world, bridging the gap between controlled labs and real-world applications like service and medical automation. His most influential work, "Go Fetch: Mobile Manipulation in Unstructured Environments" (2020, 12 citations), lays the foundation for robots to navigate and manipulate objects in cluttered, unpredictable spaces—a critical step toward practical domestic and healthcare assistants. Blomqvist also tackles the data bottleneck in robotics with "Semi-automatic 3D Object Keypoint Annotation and Detection for the Masses" (2022, 7 citations), democratizing dataset creation for object tracking and grasping. More recently, he has addressed niche but vital challenges, such as reading analog gauges in the wild ("Under pressure," 2024, 3 citations) and offline object segmentation through implicit neural representations ("NeRFing it," 2023, 2 citations). His work consistently emphasizes interpretability and deployability, ensuring that robotic systems are not only intelligent but also trustworthy and practical. Blomqvist’s contributions are shaping a future where robots seamlessly assist in everyday tasks, from reading pressure gauges to fetching objects on command.
Research Focus
Key Achievements
Top Papers
- 1Go Fetch: Mobile Manipulation in Unstructured Environments12 citations · 2020
- 2
- 3Under pressure: learning-based analog gauge reading in the wild3 citations · 2024
- 4NeRFing it: Offline Object Segmentation Through Implicit Modeling2 citations · 2023