4 citations · 17 across the 15 of their papers we have counts for
15 papers · 1 filter
Temporal Policy: History-Initialized Action Generation for Robotic Learning from Demonstration
Dylan Miller, Martin Jagersand
By relying on independent couplings from uninformative Gaussian priors, standard diffusion and flow matching models are forced to learn complex, high-cost vector fields to reach th…
Sensorless Four-Channel Control Architecture Using Inverse Dynamics Modeling for Human-Scale Bilateral Teleoperation
Amir Noohian, Dylan Miller, Justin Valentine +2
The four-channel teleoperation architecture is a well-established framework for achieving transparency in bilateral systems. However, its performance in human-scale teleoperation i…
HITL-D: Human In The Loop Diffusion Assisted Shared Control
Riley Zilka, Sergey Khlynovskiy, Allie Wang +1
Autonomous manipulation systems have achieved remarkable capabilities, yet the integration of human expertise with diffusion-based policies in shared control remains relatively une…
Revisiting Sparse Rewards for Goal-Reaching Reinforcement Learning
Gautham Vasan, Yan Wang, Fahim Shahriar +3
Many real-world robot learning problems, such as pick-and-place or arriving at a destination, can be seen as a problem of reaching a goal state as soon as possible. These problems,…
Generalizable task representation learning from human demonstration videos: a geometric approach
Jun Jin, Martin Jagersand
We study the problem of generalizable task learning from human demonstration videos without extra training on the robot or pre-recorded robot motions. Given a set of human demonstr…
Analyzing Neural Jacobian Methods in Applications of Visual Servoing and Kinematic Control
Michael Przystupa, Masood Dehghan, Martin Jagersand +1
Designing adaptable control laws that can transfer between different robots is a challenge because of kinematic and dynamic differences, as well as in scenarios where external sens…