90 citations · 175 across the 26 of their papers we have counts for
15 papers · 1 filter
DreamControl-v2: Simpler and Scalable Autonomous Humanoid Skills via Trainable Guided Diffusion Priors
Sudarshan Harithas, Sangkyung Kwak, Pushkal Katara +6
Developing robust autonomous loco-manipulation skills for humanoids remains an open problem in robotics. While RL has been applied successfully to legged locomotion, applying it to…
DreamControl: Human-Inspired Whole-Body Humanoid Control for Scene Interaction via Guided Diffusion
Dvij Kalaria, Sudarshan S Harithas, Pushkal Katara +7
We introduce DreamControl, a novel methodology for learning autonomous whole-body humanoid skills. DreamControl leverages the strengths of diffusion models and Reinforcement Learni…
Logically Constrained Robotics Transformers for Enhanced Perception-Action Planning
Parv Kapoor, Sai Vemprala, Ashish Kapoor
With the advent of large foundation model based planning, there is a dire need to ensure their output aligns with the stakeholder's intent. When these models are deployed in the re…
GRID: A Platform for General Robot Intelligence Development
Sai Vemprala, Shuhang Chen, Abhinav Shukla +2
Developing machine intelligence abilities in robots and autonomous systems is an expensive and time consuming process. Existing solutions are tailored to specific applications and…
ConBaT: Control Barrier Transformer for Safe Policy Learning
Yue Meng, Sai Vemprala, Rogerio Bonatti +2
Large-scale self-supervised models have recently revolutionized our ability to perform a variety of tasks within the vision and language domains. However, using such models for aut…
PACT: Perception-Action Causal Transformer for Autoregressive Robotics Pre-Training
Rogerio Bonatti, Sai Vemprala, Shuang Ma +3
Robotics has long been a field riddled with complex systems architectures whose modules and connections, whether traditional or learning-based, require significant human expertise…
Learning to Simulate Realistic LiDARs
Benoit Guillard, Sai Vemprala, Jayesh K. Gupta +4
Simulating realistic sensors is a challenging part in data generation for autonomous systems, often involving carefully handcrafted sensor design, scene properties, and physics mod…
LATTE: LAnguage Trajectory TransformEr
Arthur Bucker, Luis Figueredo, Sami Haddadin +4
Natural language is one of the most intuitive ways to express human intent. However, translating instructions and commands towards robotic motion generation and deployment in the r…
COMPASS: Contrastive Multimodal Pretraining for Autonomous Systems
Shuang Ma, Sai Vemprala, Wenshan Wang +4
Learning representations that generalize across tasks and domains is challenging yet necessary for autonomous systems. Although task-driven approaches are appealing, designing mode…
Adversarial Attacks on Optimization based Planners
Sai Vemprala, Ashish Kapoor
Trajectory planning is a key piece in the algorithmic architecture of a robot. Trajectory planners typically use iterative optimization schemes for generating smooth trajectories t…
AirSim Drone Racing Lab
Ratnesh Madaan, Nicholas Gyde, Sai Vemprala +7
Autonomous drone racing is a challenging research problem at the intersection of computer vision, planning, state estimation, and control. We introduce AirSim Drone Racing Lab, a s…
Safety Considerations in Deep Control Policies with Safety Barrier Certificates Under Uncertainty
Tom Hirshberg, Sai Vemprala, Ashish Kapoor
Recent advances in Deep Machine Learning have shown promise in solving complex perception and control loops via methods such as reinforcement and imitation learning. However, guara…
Collaborative Localization for Micro Aerial Vehicles
Sai Vemprala, Srikanth Saripalli
In this paper, we present a framework for performing collaborative localization for groups of micro aerial vehicles (MAV) that use vision based sensing. The vehicles are each assum…
Drone Detection Using Depth Maps
Adrian Carrio, Sai Vemprala, Andres Ripoll +2
Obstacle avoidance is a key feature for safe Unmanned Aerial Vehicle (UAV) navigation. While solutions have been proposed for static obstacle avoidance, systems enabling avoidance…
Monocular Vision based Collaborative Localization for Micro Aerial Vehicle Swarms
Sai Vemprala, Srikanth Saripalli
In this paper, we present a vision based collaborative localization framework for groups of micro aerial vehicles (MAV). The vehicles are each assumed to be equipped with a forward…