Numerical Methods for Things That Move: From Quadrupeds to Starships
Abstract: Recent advances in motion planning and control have led to dramatic successes like SpaceX’s rocket landings and Boston Dynamics’ humanoid robot acrobatics. However, the underlying numerical methods used in these applications are typically decades old, not tuned for high performance on planning and control problems, and are often unable to cope with the types [...]
Carnegie Mellon University
Combining Multiple Heuristics: Studies on Neighborhood-base Heuristics and Sampling-based Heuristics
Abstract: This thesis centers on the topic of how to automatically combine multiple heuristics. For most computationally challenging problems, there exist multiple heuristics, and it is generally the case that any such heuristic exploits only a limited number of aspects among all the possible problem characteristics that we can think of, and by definition, is [...]
Fast Foveation for LIDARs, Projectors and Cameras
Abstract: Most cameras today capture images without considering scene content. In contrast, animal eyes have fast mechanical movements that control how the scene is imaged in detail by the fovea, where visual acuity is highest. This concentrates computational (i.e. neuronal) resources in places where they are most needed. The prevalence of foveation, and the wide [...]
POSTPONED – 2020 Robotics Institute Semi-formal
Due to uncertainty and developing conditions of the coronavirus (COVID-19) outbreak, the Robotics Institute at Carnegie Mellon has determined it best to postpone our planned RI Semi-formal activity on March 20, 2020. More information will be sent out once a new date has been selected. __________________POSTPONED _____________________ By invitation only: The 2020 Robotics Institute Semi-formal [...]
Carnegie Mellon University
Robotic Grasping in the Wild
Zoom Link Abstract Robotics and artificial intelligence have witnessed tremendous progress in the past decade. Yet, we are still far from building the general purpose robot butler that can autonomously operate in homes and help with manipulation tasks like household chores. Grasping is an important action primitive for manipulation and needs to generalize to unstructured [...]
Carnegie Mellon University
Resource-constrained learning and inference for visual perception
Zoom Link Abstract Real-world applications usually require computer vision algorithms to meet certain resource constraints. In this talk, I will present evaluation methods and principled solutions for both cases of training and testing. First, I will talk about a formal setting for studying training under the non-asymptotic, resource-constrained regime, i.e., budgeted training. We analyze the [...]
Carnegie Mellon University
Multi-hypothesis iSAM2 for Ambiguity-aware Passive and Active SLAM
Archived video Abstract Simultaneous localization and mapping (SLAM) is the problem of estimating the state of a moving agent with sensors on it while simultaneously reconstructing a map of its surrounding environment, which has been a popular research field due to its wide applications. As many state-of-the-art SLAM algorithms can already achieve high accuracy in [...]
Learning to See Through Occlusions and Obstructions
Virtual VASC: https://cmu.zoom.us/j/249106600 Abstract: Photography allows us to capture and share memorable moments of our lives. However, 2D images appear flat due to the lack of depth perception and may suffer from poor imaging conditions such as taking photos through reflecting or occluding elements. In this talk, I will present our recent efforts to [...]
Carnegie Mellon University
Terrain Relative Navigation for Lunar Polar Roving: Exploiting Geometry, Shadows, and Planning
Archived Zoom Video Abstract Water ice at the lunar poles could be the most valuable resource beyond planet Earth. However, that value is not foregone, and can only be determined by rovers that evaluate the distributions of abundance, concentration, and characteristics of this ice. The near-term explorations will be solar and unlikely to endure night, [...]
Carnegie Mellon University
Resource-Constrained State Estimation with Multi-Modal Sensing
Zoom Link Accurate and reliable state estimation is essential for safe mobile robot operation in real-world environments because ego-motion estimates are required by many critical autonomy functions such as control, planning, and mapping. Computing accurate state estimates depends on the physical characteristics of the environment, the selection of suitable sensors to capture that information, and [...]