Motion planning is a cornerstone of autonomous robots, enabling robots to safely and efficiently perform tasks such as package delivery, infrastructure inspection, and manipulation. However, as the field of robotics matures, robotic systems are being developed that (1) are challenging to analytically model, (2) require computationally expensive model-based controllers, and...
Human-robot teams involve humans and robots collaborating to achieve tasks under various environmental conditions. Successful teaming requires robots to adapt autonomously in real-time to a human teammate's state. An important element of such adaptation is the ability for the robot to infer the tasks performed by their human teammates. Human-robot...
Legged robots have consistently captured our collective imagination through various forms of media, from Hollywood films, anime, and viral Youtube videos of robots accomplishing incredible feats of acrobatics. These robots have the potential to navigate our environments, capable of completing tasks that would otherwise require human intervention. However, developing controls...
Multiagent learning offers a rich framework to address challenging real-world problems such as remote exploration and healthcare coordination, which require autonomous agents to express elaborate interactions. To be effective in such systems, agents must collectively reason about and pursue high-level, long-term, and possibly nebulous objectives while adapting their strategy to...
Disaster response and surveillance operations will increasingly incorporate Unmanned Aerial Vehicles (UAV)s due to their cost-effectiveness and maneuverability. This trend has driven the research on small-sized quadcopters for varying indoor applications. Small-sized quadcopters' payload and computational capacity limit the usage of complex vision-based collision avoidance algorithms that are employed by...
Multiagent approaches are well suited to designing autonomous solutions for systems that feature complex interactions between many individuals such as in autonomous traffic systems and multi-robot exploration systems. However, creating autonomous agents that function effectively in these systems is a challenging task. In these complex environments, agents need informative reward...
Successful pruning relies on accurately identifying the 3D structure of tree branches and leaders. However, this task is arduous in an agricultural setting due to the complexity of scenes, the presence of clutter, and variable weather conditions. This project addresses these challenges by leveraging advancements in 2D image segmentation and...
Expressive motion has been found to be a highly effective tool in communicating intent and motivation in single robot human-robot interaction, but work in exploring how groups of robots can use motion in interactions with humans is relatively nascent. There are many additional complexities to consider expanding from single robot...
In recent years, model-free Deep Reinforcement Learning (RL) has become an increasingly popular alternative to more traditional model-based or optimization-based control methods in solving robotic legged locomotion. However, deploying RL in the real world can be a significant undertaking. Constructing reward functions which compel controllers to learn the desired behavior...
Fingered robot hands are complicated systems made of three essential system components: its morphology, its actuation, and its software control. These system components are tightly coupled to each other. Due to this, it is hard to benchmark robot hand performance in a way to understand the contributions of the individual...