103 citations · 110 across the 9 of their papers we have counts for
9 papers
Safe Model Predictive Diffusion with Shielding
Taekyung Kim, Keyvan Majd, Hideki Okamoto +3
Generating safe, kinodynamically feasible, and optimal trajectories for complex robotic systems is a central challenge in robotics. This paper presents Safe Model Predictive Diffus…
GPU-Accelerated Barrier-Rate Guided MPPI Control for Tractor-Trailer Systems
Keyvan Majd, Hardik Parwana, Bardh Hoxha +3
Articulated vehicles such as tractor-trailers, yard trucks, and similar platforms must often reverse and maneuver in cluttered spaces where pedestrians are present. We present how…
Repairing Neural Networks for Safety in Robotic Systems using Predictive Models
Keyvan Majd, Geoffrey Clark, Georgios Fainekos +1
This paper introduces a new method for safety-aware robot learning, focusing on repairing policies using predictive models. Our method combines behavioral cloning with neural netwo…
Open X-Embodiment: Robotic Learning Datasets and RT-X Models
Embodiment Collaboration, Abby O'Neill, Abdul Rehman +291
Large, high-capacity models trained on diverse datasets have shown remarkable successes on efficiently tackling downstream applications. In domains from NLP to Computer Vision, thi…
Certifiably-correct Control Policies for Safe Learning and Adaptation in Assistive Robotics
Keyvan Majd, Geoffrey Clark, Tanmay Khandait +4
Guaranteeing safety in human-centric applications is critical in robot learning as the learned policies may demonstrate unsafe behaviors in formerly unseen scenarios. We present a…
Safe Robot Learning in Assistive Devices through Neural Network Repair
Keyvan Majd, Geoffrey Clark, Tanmay Khandait +4
Assistive robotic devices are a particularly promising field of application for neural networks (NN) due to the need for personalization and hard-to-model human-machine interaction…
Local Repair of Neural Networks Using Optimization
Keyvan Majd, Siyu Zhou, Heni Ben Amor +2
In this paper, we propose a framework to repair a pre-trained feed-forward neural network (NN) to satisfy a set of properties. We formulate the properties as a set of predicates th…
Joint Communication and Motion Planning for Cobots
Mehdi Dadvar, Keyvan Majd, Elena Oikonomou +2
The increasing deployment of robots in co-working scenarios with humans has revealed complex safety and efficiency challenges in the computation robot behavior. Movement among huma…
Safe Navigation in Human Occupied Environments Using Sampling and Control Barrier Functions
Keyvan Majd, Shakiba Yaghoubi, Tomoya Yamaguchi +3
Sampling-based methods such as Rapidly-exploring Random Trees (RRTs) have been widely used for generating motion paths for autonomous mobile systems. In this work, we extend time-b…