1 citations · 3 across the 6 of their papers we have counts for
8 papers
Training Generalist Navigation Policies via Action Self-Distillation
Bowen Feng, Keqin Wang, Yulong Yang +4
Language provides a natural interface for humans to specify and reason about goals, but training language-conditioned robotic policies and reasoning typically requires expensive ma…
GLAMDRING: Gait Learning And Morphology co-Design via Reinforcement LearnING of CPGs
Amogh Joshi, Kaushik Roy
Robots are moving out of the structured factory floor and into unstructured environments such as disaster sites, planetary surfaces, and agricultural fields, for which the right ro…
Real-Time Neuromorphic Navigation: Guiding Physical Robots with Event-Based Sensing and Task-Specific Reconfigurable Autonomy Stack
Sourav Sanyal, Amogh Joshi, Adarsh Kosta +1
Neuromorphic vision, inspired by biological neural systems, has recently gained significant attention for its potential in enhancing robotic autonomy. This paper presents a systema…
Energy-Efficient Autonomous Aerial Navigation with Dynamic Vision Sensors: A Physics-Guided Neuromorphic Approach
Sourav Sanyal, Amogh Joshi, Manish Nagaraj +2
Vision-based object tracking is a critical component for achieving autonomous aerial navigation, particularly for obstacle avoidance. Neuromorphic Dynamic Vision Sensors (DVS) or e…
TOFFE -- Temporally-binned Object Flow from Events for High-speed and Energy-Efficient Object Detection and Tracking
Adarsh Kumar Kosta, Amogh Joshi, Arjun Roy +3
Object detection and tracking is an essential perception task for enabling fully autonomous navigation in robotic systems. Edge robot systems such as small drones need to execute c…
Neuro-LIFT: A Neuromorphic, LLM-based Interactive Framework for Autonomous Drone FlighT at the Edge
Amogh Joshi, Sourav Sanyal, Kaushik Roy
The integration of human-intuitive interactions into autonomous systems has been limited. Traditional Natural Language Processing (NLP) systems struggle with context and intent und…
SHIRE: Enhancing Sample Efficiency using Human Intuition in REinforcement Learning
Amogh Joshi, Adarsh Kumar Kosta, Kaushik Roy
The ability of neural networks to perform robotic perception and control tasks such as depth and optical flow estimation, simultaneous localization and mapping (SLAM), and automati…
Real-Time Neuromorphic Navigation: Integrating Event-Based Vision and Physics-Driven Planning on a Parrot Bebop2 Quadrotor
Amogh Joshi, Sourav Sanyal, Kaushik Roy
In autonomous aerial navigation, real-time and energy-efficient obstacle avoidance remains a significant challenge, especially in dynamic and complex indoor environments. This work…