11 accepted papers
Multi-robot motion planning and crowd simulations are crucial in social navigation, enabling agents to avoid collisions with one another in dynamic environments. While existing methods typically use simple circular models for robot and pedestrian boundaries, superquadric models offer greater flexibi…
Probabilistic collision detection (PCD) is essential in motion planning for robots operating in unstructured environments, where considering sensing uncertainty helps prevent damage. Existing PCD methods mainly used simplified geometric models and addressed only position estimation errors. This pape…
Safe and efficient obstacle avoidance in multi-robot navigation is a challenging problem, with deadlock being a key issue due to strict collision-free constraints. This paper proposes a novel Lateral Reciprocal Collision Avoidance (LRCA) strategy based on velocity obstacle theory to mitigate deadloc…
This paper proposes a learning-from-demonstration (LfD) method using probability densities on the workspaces of robot manipulators. The method, named PRobabilistically-Informed Motion Primitives (PRIMP), learns the probability distribution of the end effector trajectories in the 6D workspace that in
Representing complex objects with basic geometric primitives has long been a topic in computer vision. Primitive-based representations have the merits of compactness and computational efficiency in higher-level tasks such as physics simulation, collision checking, and robotic manipulation. Unlike pr…
In this letter, a paradigm for the classification and manipulation of novel objects is established and demonstrated with the example of chairs. Our approach leverages the robot's understanding of object stability, perceptibility, and affordance to prepare previously unseen and randomly oriented chai
This paper studies the narrow phase collision detection problem for two general unions of convex bodies encapsulated by smooth surfaces. The approach, namely <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">CFC</i> (Closed-Form Contact space), is base
"3D shape abstraction has drawn great interest over the years. Apart from low-level representations such as meshes and voxels, researchers also seek to semantically abstract complex objects with basic geometric primitives. Recent deep learning methods rely heavily on datasets, with limited generalit…
In this paper, we study the problem of autonomously seating a teddy bear on a previously unseen chair. To achieve this goal, we present a novel method for robots to imagine the sitting pose of the bear by physically simulating a virtual humanoid agent sitting on the chair. We also develop a robotic…
Interpreting objects with basic geometric primitives has long been studied in computer vision. Among geometric primitives, superquadrics are well known for their ability to represent a wide range of shapes with few parameters. However, as the first and foremost step, recovering superquadrics accurat…
Collision detection has attracted attention of researchers for decades in the field of computer graphics, robot motion planning, computer aided design, etc. A large number of successful algorithms have been proposed and applied, which make use of convex polytopes and bounding volumes as primitives.…