Learning meaningful visual representations in an embedding space can facilitate
generalization in downstream tasks such as action segmentation and imitation. In this paper …

When providing task demonstrations to a remote robot over the network via bilateral
teleoperation, communication impairments are unavoidable, hindering the human operator …

This paper presents a framework to learn the sequential structure in the demonstrations for
robot imitation learning. We first present a family of task-parameterized hidden semi-Markov …

For performing robotic manipulation tasks, the core problem is determining suitable
trajectories that fulfill the task requirements. Various approaches to compute such …

Advanced wireless communication networks provide lower latency and a higher
transmission rate. Although this is an enabler for many new teleoperation applications, the …

This study addresses the problem of sliding mode control (SMC) for networked non-
homogeneous hidden semi-Markov switching systems under semi-Markov kernel and cyber …

In this paper, we aim to expedite the deployment of challenging manipulation tasks involving
both motion and contact wrenches (forces and moments). To this end, we acquire motion …

Network latency is a major problem in Cloud Robotics for human robot interaction such as
tele-operation. Routing delays can be highly variable in a heterogeneous computing …

Understanding the kinematics of a ground robot is essential for efficient navigation. Based
on the kinematic model of a robot, its full motion capabilities can be represented by …

Path planning is an essential component of autonomous driving. A global planner is
responsible for the high-level planning. It basically performs a shortest-path search on a …