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Found 13 papers, 4 papers with code
Enhancing Navigation Benchmarking and Perception Data Generation for Row-based Crops in Simulation
Service robotics is recently enhancing precision agriculture enabling many automated processes based on efficient autonomous navigation solutions.
Domain Generalization for Crop Segmentation with Standardized Ensemble Knowledge Distillation
Our approach provides a promising solution for domain generalization in crop segmentation and has the potential to enhance a wide variety of agriculture applications.
Online Learning of Wheel Odometry Correction for Mobile Robots with Attention-based Neural Network
Modern robotic platforms need a reliable localization system to operate daily beside humans.
PIC4rl-gym: a ROS2 modular framework for Robots Autonomous Navigation with Deep Reinforcement Learning
Learning agents can optimize standard autonomous navigation improving flexibility, efficiency, and computational cost of the system by adopting a wide variety of approaches.
Deep Instance Segmentation and Visual Servoing to Play Jenga with a Cost-Effective Robotic System
A Jenga game round undoubtedly embeds many traits of complex industrial or surgical manipulation tasks, requiring a multi-step strategy, the combination of visual and tactile data, and the highly precise motion of the robotic arm to perform a single block extraction.
RL-DWA Omnidirectional Motion Planning for Person Following in Domestic Assistance and Monitoring
Our methodology exploits an omnidirectional robotic platform to detach the computation of linear and angular velocities and navigate within the domestic environment without losing track of the assisted person.
Generative Adversarial Super-Resolution at the Edge with Knowledge Distillation
Single-Image Super-Resolution can support robotic tasks in environments where a reliable visual stream is required to monitor the mission, handle teleoperation or study relevant visual details.
Back-to-Bones: Rediscovering the Role of Backbones in Domain Generalization
Domain Generalization (DG) studies the capability of a deep learning model to generalize to out-of-training distributions.
Position-Agnostic Autonomous Navigation in Vineyards with Deep Reinforcement Learning
Precision agriculture is rapidly attracting research to efficiently introduce automation and robotics solutions to support agricultural activities.
Waypoint Generation in Row-based Crops with Deep Learning and Contrastive Clustering
In this paper, we propose a learning-based approach to tackle waypoint generation for planning a navigation path for row-based crops, starting from a top-view map of the region-of-interest.
Marvin: an Innovative Omni-Directional Robotic Assistant for Domestic Environments
Despite these emerging needs, in the actual landscape of robotic assistants there are no platform which successfully combines a reliable mobility in cluttered domestic spaces, with lightweight and offline Artificial Intelligence (AI) solutions for perception and interaction.
A Deep Learning Driven Algorithmic Pipeline for Autonomous Navigation in Row-Based Crops
Expensive sensors and inefficient algorithmic pipelines significantly affect the overall cost of autonomous machines.
Domain-Adversarial Training of Self-Attention Based Networks for Land Cover Classification using Multi-temporal Sentinel-2 Satellite Imagery
The increasing availability of large-scale remote sensing labeled data has prompted researchers to develop increasingly precise and accurate data-driven models for land cover and crop classification (LC&CC).
