In recent years, a large number of manipulator robots have been deployed to replace or
assist humans in many repetitive and dangerous tasks. Yet, these robots have complex …

We present a manipulation planning framework that allows robots to plan in the presence of
constraints on end-effector pose, as well as other common constraints. The framework has …

Aiming to realize the obstacle avoidance of the litchi-picking robot in dynamic and
unstructured environments, an improved rapidly exploring random tree (RRT) algorithm is …

In unstructured environments, picking robots could collide with branches, thus reducing the
success rate of picking. In this study, collision-free motion planning is performed in two steps …

Grasping an object is a task that inherently needs to be treated in a hybrid fashion. The
system must decide both where and how to grasp the object. While selecting where to grasp …

We present the hardware design, software architecture, and core algorithms of Herb 2.0, a
bimanual mobile manipulator developed at the Personal Robotics Lab at Carnegie Mellon …

We present an approach to path planning for manipulators that uses Workspace Goal
Regions (WGRs) to specify goal end-effector poses. Instead of specifying a discrete set of …

We introduce a method for task-oriented design of concentric tube robots, which are tentacle-
like robots with the potential to enable new minimally invasive surgical procedures. Our …

This paper proposes a model-free control framework for the path planning of the rigid and
soft robotic manipulator using an intelligent algorithm called Weighted Jacobian Rapidly …

We present a sampling-based path planning algorithm capable of efficiently generating
solutions for high-dimensional manipulation problems involving challenging inverse …