The objective of this paper is to propose a framework for a robot to learn multiple Sensory-
Motor Contingencies from human demonstrations and reproduce them. Sensory-Motor …

Recent analyses by leading national wildfire and emergency monitoring agencies have
highlighted an alarming trend: the impact of wildfire devastation has escalated to nearly …

In this paper, a feature extraction approach for the deformable linear object is presented,
which uses a Bezier curve to represent the original geometric shape. The proposed …

This paper introduces a manipulation framework for the elastic rod, including shape
representation, sensorimotor-model estimation, and shape controller. Until now, the …

In this paper, we introduce CrimeGraphNet, a novel approach for link prediction in criminal
networks utilizingGraph Convolutional Networks (GCNs). Criminal networks are intricate and …

In this paper, we present CrimeGAT, a novel application of Graph Attention Networks (GATs)
for predictive policing in criminal networks. Criminal networks pose unique challenges for …

Large language models (LLMs) have made significant strides in various applications, but
optimizing their task planning capabilities remains a critical challenge. To address this, we …

Recent advances in soft robotics have opened up new possibilities for delicate manipulation
tasks in unstructured environments. Soft manipulators exhibit highly deformable structures …

Robotic manipulation of deformable objects presents a challenging problem due to their
complex and unpredictable nature. Traditional control methods often struggle to handle the …

This research paper investigates the influence of latent and semantic representation
frameworks on the efficacy of robotic grasping and manipulation, particularly focusing on soft …