The Robot Perception Lab performs research related to localization, mapping and state estimation for autonomous mobile robots. The lab was founded in 2014 by Prof. Michael Kaess. The lab is part of the Robotics Institute at Carnegie Mellon University and belongs to both the Field Robotics Center and the Computer Vision Group.
Applications of our research span a wide range from underwater robots to aerial robots and handheld systems for mapping.
Group photos 2018 (left) and 2016 (right)
- Jerry’s paper on information sparsification in visual-inertial odometry was one of six finalists for the best IROS 2018 conference paper.
- New RI seminar on factor graphs in robot perception.
- We have presented 4 papers at IROS 2018 in Madrid, Spain: Virtual occupancy grid maps, multi-beam sonar processing, information sparsification in visual-inertial odometry, and lidar-camera calibration.
- We have presented 3 papers at ICRA 2018 in Brisbane, Australia: Dense planar-inertial SLAM with structural constraints, feature-based SLAM for imaging sonar, and pose-graph SLAM using forward looking sonar (also in RA-L).
- Our GravityFusion work appeared at IROS 2017 in Vancouver.
- Our new water tank is now in operation.
- At IROS 2017 we have organized a workshop on Lines, Planes, Manhattan Models for 3D Mapping and presented our work on GravityFusion.
- We have published an extended article on Factor Graphs for Robot Perception.
- We have presented 4 publications at ICRA 2017 in Singapore: Keyframe-based dense planar SLAM, manifold particle filter for state estimation under contact, robust stereo matching, and direct visual odometry using binary descriptors
- We have presented 5 publications at IROS 2016 in Daejeon, South Korea: GPS-denied long distance flight, inference with multimodal posteriors, data association for ASFM, underwater mapping, and monocular planar mapping.