PhD Thesis Defense
Robotics Institute,
Carnegie Mellon University

Coordinated online multi-robot planning

Abstract: Multi-robot applications frequently seek to employ human operators to direct robot actions online because fully automated planners struggle to encode human expertise or handle the extenuating circumstances that occur during real world operations. However, it is extremely challenging for a human to direct multi-robot teams, especially online, i.e., in real-time. From entertainment to defense, [...]

PhD Thesis Defense
Postdoctoral Fellow
Robotics Institute,
Carnegie Mellon University

Sensor Planning for Large Numbers of Robots

Abstract: In the wake of a natural disaster, locating and extracting victims quickly is critical because mortality rises rapidly after the first forty-eight hours. In order to assist search and rescue teams and improve response times, teams of aerial robots equipped with sensors and cameras can engage in sensing tasks such as mapping buildings, assessing [...]

PhD Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

3D Multi-Object Tracking for Autonomous Driving

Abstract: 3D multi-object tracking (MOT) is a key component of a perception system for autonomous driving. Due to recent progress in 3D object detection in the context of autonomous driving, recent work in 3D MOT primarily focuses on online tracking with the use of a tracking-by-detection pipeline. In this talk, we introduce a new 3D [...]

PhD Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

Ergodic Trajectory Optimization for Information Gathering

Abstract: Planetary robots currently rely on significant guidance from expert human operators. Science autonomy adds algorithms and methods for autonomous scientific exploration to improve efficiency of discovery and overcome limited communication bandwidth and delay bottlenecks. This research focuses on planning trajectories for information gathering and choosing sampling locations that have the most informative samples. We [...]

PhD Thesis Proposal
Robotics Institute,
Carnegie Mellon University

Planning and Execution using Inaccurate Models with Provable Guarantees on Task Completeness

Abstract: Modern planning methods are effective in computing feasible and optimal plans for robotic tasks when given access to accurate dynamical models. However, robots operating in the real world often face situations that cannot be modeled perfectly before execution. Thus, we only have access to simplified but potentially inaccurate models. This imperfect modeling can lead [...]

PhD Thesis Defense
Robotics Institute,
Carnegie Mellon University

Constraint-Based Coverage Path Planning: A Novel Approach to Achieving Energy-Efficient Coverage

Abstract: Despite substantial technological progress that has driven the proliferation of robots across various industries and aspects of our lives, the lack of a decisive breakthrough in energy storage capabilities has restrained this trend, particularly with respect to mobile robots designed for use in unstructured and unknown field environments. The fact that these domains are [...]

PhD Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

Residual Force Control for Agile Human Behavior Imitation and Extended Motion Synthesis

Abstract: Reinforcement learning has shown great promise for synthesizing realistic human behaviors by learning humanoid control policies from motion capture data. However, it is still very challenging to reproduce sophisticated human skills like ballet dance, or to stably imitate long-term human behaviors with complex transitions. The main difficulty lies in the dynamics mismatch between the [...]

PhD Speaking Qualifier
Extern
Robotics Institute,
Carnegie Mellon University

Studying the Evolution of Pedestrian Group Space

Abstract: Imagine walking along a busy sidewalk, do you track the movement of every single individual? Or do you simply group pedestrians with similar moving patterns and then track the movement of this group? Grouping is a common behavior in pedestrian navigation and it is typically inappropriate for a robot to cut through the social [...]

PhD Thesis Defense
Robotics Institute,
Carnegie Mellon University

Unsupervised Learning of the 4D Audio-Visual World from Sparse Unconstrained Real-World Samples

Abstract: We, humans, can easily observe, explore, and analyze the world we live in. We, however, struggle to share our observation, exploration, and analysis with others. This thesis introduce Computational Studio, computational machinery that can understand, explore, and create the four-dimensional audio-visual world. This allows: (1) humans to communicate with other humans without any loss [...]

MSR Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

Xueting Li – MSR Thesis Talk

Zoom

Title: Multi-agent Deception in Attack-Defense Stochastic Game   Abstract: In adversarial scenarios, defending oneself by using deception has recently been studied. A popular direction is to design deceptive defense strategies when the defender has complete information of the game and the attacker doesn't. The work on deception so far models the games as a signal game [...]