Max Robotics — Global Service Robot Directory + US Certification

About

Budianto Tandianus is a researcher at the forefront of robotic perception and autonomous navigation, specializing in 3D object detection, semantic mapping, and visual relocalization for indoor service robots. His work addresses a critical challenge: enabling robots to understand and interact with cluttered, dynamic environments at a human-like semantic level. Tandianus pioneered multi-view fusion and multi-channel convolutional neural network (CNN) architectures for 3D object detection, allowing robots to perceive incomplete objects and extract high-level semantics from raw sensor data—a leap beyond traditional geometric reconstruction. His most cited paper, “Multi-View Fusion-Based 3D Object Detection for Robot Indoor Scene Perception” (28 citations), and its companion work (24 citations) have become foundational references for researchers tackling robot environmental perception. Tandianus also introduced the concept of an object-aware hybrid map, which integrates semantic object information with metric maps to enable intuitive visual semantic navigation. Additionally, his work on image-similarity-based CNNs for visual relocalization improved pose estimation robustness from single RGB images. With a growing citation impact, Tandianus’s contributions are shaping the next generation of intelligent, perceptive service robots capable of long-term autonomous operation in human-centric spaces.