MSR Speaking Qualifier

Title: Spatiotemporal Modeling using Recurrent Neural Processes   Abstract: Spatiotemporal processes, such as temperature in an area, motion of a vehicle, etc., depend on the spatial features of the underlying phenomena as well as time. Developing models that can estimate both mean and uncertainty associated with the prediction is important for building robust systems capable of [...]

Title: Localization and Active Exploration in Indoor Underwater Environments Abstract: Autonomous underwater vehicles have the potential to inspect and map indoor underwater environments, such as spent nuclear fuel pools and ship ballast tanks. Towards this, the thesis makes contributions in the domains of visual localization and active SLAM for underwater environments. In the first work, [...]

Title: Multi-Sensor Fusion for Robust Simultaneous Localization and Mapping   Abstract:  Simultaneous Localization and Mapping (SLAM) consists of the estimation of the state of the robot, and the reconstruction of the surrounding environment simultaneously. Over the last few decades, numerous state-of-the-art SLAM algorithms are proposed and frequently utilized in the robotics community. However, a SLAM algorithm [...]

Title: State Estimation for Legged Robots using Proprioceptive Sensors   Abstract:  Mobile robots need good estimates of their state to perform closed-loop control in structured and unstructured environments. A number of existing algorithms rely on data fusion from multiple sensors to compute these estimates. This work focuses on state estimation using sensors which only measure [...]

Title: Leveraging Computer Vision and Reinforcement Learning for contact and non-contact based plant phenotyping.     Abstract:  Effective plant breeding requires scientists to find correspondences between genetic markers and desirable physical traits (phenotypes) of the genotype. Robotics can aid the acceleration of breeding pipeline by facilitating high throughput plant phenotyping. In this thesis we propose [...]

Title: Active Sampling for Planetary Rover Exploration Abstract: Planetary Robotics research has expanded beyond simply developing robust navigation strategies for rovers to providing them with the capability of performing intelligent actions so as to develop a better interpretation and understanding of the environment. This will become essential in the future, when rovers explore regions far [...]

Title:  Efficient Planning for High-Speed MAV Flight in Unknown Environments Using Sparse Topological Graphs   Abstract: Safe high-speed autonomous navigation for MAVs in unknown environments requires fast planning to enable the robot to adapt and react quickly to incoming information about obstacles within the world.  Furthermore, when operating in environments not known a priori, the robot [...]

Title: Recognizing Tiny Faces Abstract: Objects are naturally captured over a continuous range of distances, causing dramatic changes in appearance, especially at low resolutions. Recognizing such small objects at range is an open challenge in object recognition. In this paper, we explore solutions to this problem by tackling the fine-grained task of face recognition. State-of-the-art embeddings [...]

Title: Design and Control of a Large Modular Hexapod   Abstract: Legged robotic systems have made great strides in recent years, but unlike wheeled robots, limbed locomotion does not scale well.  Long legs demand huge torques, driving up actuator size and onboard battery mass.  This relationship results in massive structures that lack the safety, portability, [...]

Title: Combining Deep Learning and Verification for Precise Object Instance Detection   Abstract: Deep learning based object detectors often return false positives with very high confidence. Although they optimize generic detection performance, such as mean average precision (mAP), they are not designed for reliability. For a reliable detection system, if a high confidence detection is [...]