Student Talks
Indoor Localization and Mapping with 4D mmWave Imaging Radar
Abstract: State estimation is a crucial component for the successful implementation of robotic systems, relying on sensors such as cameras, LiDAR, and IMUs. However, in real-world scenarios, the performance of these sensors is degraded by challenging environments, e.g. adverse weather conditions and low-light scenarios. The emerging 4D imaging radar technology is capable of providing robust perception in adverse conditions. [...]
PIE-FRIDA: Personalized Interactive Emotion-Guided Collaborative Human-Robot Art Creation
Abstract: The introduction of generative AI has brought about many improvements in the artistic world. It allows many individuals to create artwork via simple descriptive text prompts. This has, in particular, created an avenue for non-artistic individuals to express their thoughts through generated art. Our work focuses on how emotion can be added as an [...]
Carnegie Mellon University
Spectral Mapping using Simple Sensors
Abstract: Spectral mapping holds significant importance in many exploration endeavors as it facilitates a deeper comprehension of material composition within a surveyed area. While imaging spectrometers excel in recording reflectance spectra into spectral maps, their large physical footprint, substantial power requirements, and operational intricacies render them unsuitable for integration into small rovers or resource-constrained missions. [...]
Simulated Encounters of the Third Kind: Scenario-Based Approach to Designing Guide Robots
Abstract: Navigating through unfamiliar environments is a challenging task. For people who are blind or have low vision (BLV), navigation can be particularly daunting. Guide robots are a type of service robot that can assist BLV people with navigation tasks. A significant amount of research related to guide robots has focused on technical contributions, while a [...]
Composing Generative and Discriminative Models for Better Generalization
Abstract: Computer Vision is Correspondence, correspondence, correspondence! Inspite of the singular definition of computer vision, we still have two broad categories of approaches in the literature. Generative Models, like Stable Diffusion, learn a correspondence between image and text modality, while learning a mapping from text to image. Discriminative Models, like CLIP, on the other hand [...]
Lower Bounds for Moving Target Traveling Salesman Motion Planning with Obstacles
Abstract: We study the problem of finding a trajectory for an agent to intercept a number of moving targets while avoiding obstacles. Applications include resupplying naval ships at sea and recharging aerial vehicles with a ground vehicle. We model the problem as an extension of the traveling salesman problem, which we refer to as the [...]
Towards Pragmatic Time Series Intelligence
Abstract: The widespread adoption of time series machine learning (ML) models faces multiple challenges involving data, modeling and evaluation. Data. Modern ML models depend on copious amounts of cohesive and reliably annotated data for training and evaluation. However, labeled data is not always available and reliable, and can also be dispersed across different locations. We [...]
Probabilistic 3D Multi-Object Cooperative Tracking for Autonomous Driving via Differentiable Multi-Sensor Kalman Filter
Abstract: Current state-of-the-art autonomous driving vehicles mainly rely on each individual sensor system to perform perception tasks. Such a framework's reliability could be limited by occlusion or sensor failure. To address this issue, more recent research proposes using vehicle-to-vehicle (V2V) communication to share perception information with others. However, most relevant works focus only on cooperative [...]
Super Odometry: Selective Fusion Towards All-degraded Environments
Abstract: Robust odometry is at the core of robotics and autonomous systems operating navigation, exploration, and locomotion in complex environments for a broad spectrum of applications. While great progress has been made, the robustness of the odometry system still remains a grand challenge. This talk introduces Super Odometry, an approach that leverages selective fusion to [...]
Improved Surface Estimation for use in Virtual Fixtures during Retinal Surgery
Abstract: Retinal surgery procedures require surgeons to manipulate very delicate tissues with little room for error. During epiretinal membrane surgery, to reduce chances of recurrence, surgeons may have to remove the 10 µm thick internal limiting membrane from the retinal surface. An experimental procedure to treat retinal vein occlusion is retinal vein cannulation. During this [...]