MEAM Ph.D. Thesis Defense: “Design and Self-Reconfiguration Planning for Variable Topology Truss Robots”
A modular self-reconfigurable robot (MSRR) is a set of robotic building blocks that can be connected together in different ways. By rearranging these connections, the robot can adapt its shape […]
MEAM Seminar: “Multi-robot Coordination Via Graph-based Computation”
Multi-robot coordination and cooperation are critical behaviors that improve team performance and enable new tasks in application areas like autonomous construction, agriculture, and extended operation in large unknown regions. This […]
MEAM Ph.D. Thesis Defense: “Addressing Stiffness-induced Challenges In Modeling and Identification of Rigid Body Systems with Frictional Impact”
Imperfect but useful dynamical models have enabled significant progress in planning and controlling robotic locomotion and manipulation. Traditionally, these models have been physics-based, with accuracy relying upon manual calibration only […]
MEAM Seminar: “Computationally-constrained Dynamically-feasible Search-based Motion Planning”
Planning fast and autonomous robotic motion in unstructured, cluttered environments remains a core challenge of the robotics community. The robot’s motion must be agile and dynamic, operating near the limit […]
5th Annual Learning for Dynamics & Control Conference
Over the next decade, the biggest generator of data is expected to be devices that sense and control the physical world. The explosion of real-time data that is emerging from […]
MEAM Seminar: “Progress on Templates for Spined and Tailed Legged Robots”
By mirroring the success of biological systems, legged robots have the potential to be successful in almost every terrestrial environment. While legged machines have made significant advancements in the past […]
MEAM Seminar: “Addressing Sensitivity-Induced Challenges in Modeling Rigid-Body Systems with Frictional Impacts”
Imperfect but useful physical models play a crucial role in planning and controlling robot locomotion and manipulation. However, as the field shifts toward complex real-world applications, model accuracy requirements are […]
ASSET Seminar: , Dinesh Jayaraman (University of Pennsylvania)
ABSTRACT: An important goal of the field sensorimotor robot learning is to do away with cumbersome expertise-intensive task specification, so that general-purpose robots of the future might learn large numbers […]
MEAM Ph.D. Thesis Defense: “An Aquatic Underactuated Modular Self-Reconfigurable Robotic System for Information-Limited Navigation in Gyre-Like Flows”
Aquatic modular self-reconfigurable robotic systems (MSRRs) have incredible potential for bringing practical, flexible, and adaptable robotic tools to challenging environments. They could build mobile ocean platforms or bridges for larger […]
A Celebration of the Life of Dr. Max Mintz
The CIS Department and GRASP Lab invite you to please join us on Thursday, November 17th, at 3:30pm as we celebrate the life and legacy of Dr. Max Mintz, Professor […]