Discovery of fundamental principles which govern and limit effective locomotion (self-
propulsion) is of intellectual interest and practical importance. Human technology has …

Recent advances in mobility, manipulation, and intelligence of robots have promoted the
usability of humanoid robots to support humans in their daily lives in the future. The multi …

This paper describes a collection of optimization algorithms for achieving dynamic planning,
control, and state estimation for a bipedal robot designed to operate reliably in complex …

The Inverse Kinematics (IK) algorithms implemented in the open-source Orocos Kinematics
and Dynamics Library (KDL) are arguably the most widely-used generic IK solvers …

Many important geometric estimation problems naturally take the form of synchronization
over the special Euclidean group: estimate the values of a set of unknown group elements x …

To plan dynamic, whole-body motions for robots, one conventionally faces the choice
between a complex, full-body dynamic model containing every link and actuator of the robot …

The ever-increasing complexity of robot applications induces the need for methods to
approach problems with no (viable) analytical solution. Deep learning (DL) provides a set of …

We present a new method for planning footstep placements for a robot walking on uneven
terrain with obstacles, using a mixed-integer quadratically-constrained quadratic program …

We present a review and reformulation of manifold constrained sampling-based motion
planning within a unifying framework, IMACS (implicit manifold configuration space). IMACS …

Common methods for learning robot dynamics assume motion is continuous, causing
unrealistic model predictions for systems undergoing discontinuous impact and stiction …