5 papers
GelSLAM: A Real-time, High-Fidelity, and Robust 3D Tactile SLAM System
Hung-Jui Huang, Mohammad Amin Mirzaee, Michael Kaess +1
Accurately perceiving an object's pose and shape is essential for precise grasping and manipulation. Compared to common vision-based methods, tactile sensing offers advantages in p…
FORM: Fixed-Lag Odometry with Reparative Mapping utilizing Rotating LiDAR Sensors
Easton R. Potokar, Taylor Pool, Daniel McGann +1
Light Detection and Ranging (LiDAR) sensors have become a de-facto sensor for many robot state estimation tasks, spurring development of many LiDAR Odometry (LO) methods in recent…
COSMO-Bench: A Benchmark for Collaborative SLAM Optimization
Daniel McGann, Easton R. Potokar, Michael Kaess
Recent years have seen a focus on research into distributed optimization algorithms for multi-robot Collaborative Simultaneous Localization and Mapping (C-SLAM). Research in this d…
A Comprehensive Evaluation of LiDAR Odometry Techniques
Easton Potokar, Michael Kaess
Light Detection and Ranging (LiDAR) sensors have become the sensor of choice for many robotic state estimation tasks. Because of this, in recent years there has been significant wo…
NormalFlow: Fast, Robust, and Accurate Contact-based Object 6DoF Pose Tracking with Vision-based Tactile Sensors
Hung-Jui Huang, Michael Kaess, Wenzhen Yuan
Tactile sensing is crucial for robots aiming to achieve human-level dexterity. Among tactile-dependent skills, tactile-based object tracking serves as the cornerstone for many task…