Dragos Calin
@calinrobotics
Since 2011, I have designed and built autonomous systems for agriculture and artificial intelligence applications.
🤹♀️As it is in reinforcement learning, so it is in life. If the reward is too far away, the agent gives up! #ReinforcementLEarning
Everyone talks about training agents. Almost no one talks about defining the application. And that’s exactly why most reinforcement learning projects fail silently. medium.com/@calinezul/cla… #ReinforcementLEarning #Robotics
The Markov Decision Process is not reality, it’s a story you tell about reality medium.com/@calinezul/the… #ArtificialInteligence #ReinforcementLEarning #Robotics
Most of the genius in RL is not in algorithms but in reward shaping, debugging, and iterating on what you actually want the agent to learn. Is that so? #reinforcementlearning #robotics #AI
I just published Why I Chose DQN for My Deep RL Agent (And Why It Was the Right Call) medium.com/p/why-i-chose-… #ArtificialInteligence #reinforcementlearning
🚀 Struggling to define your RL problem? In this guide, I share a simple method to define your Reinforcement Learning problem — using a clear checklist of essential questions. reinforcementlearningpath.com/problem-defini… #DeepLearning #ReinforcementLearning #MachineLearning
🚀reinforcementlearningpath.com – a blog fully dedicated to Deep Reinforcement Learning, explained step by step. 🎯 My mission? To make RL practical, understandable, and accessible for students, hobbyists, and engineers. #ReinforcementLearning #DeepRL #MachineLearning #Robotics
📍 Motion Model vs. Measurement Model in Localization 📍 The Motion Model predicts movement using internal sensors but accumulates errors over time. The Measurement Model corrects these errors using external references. Both are essential for accurate positioning & orientation…
I just published Why Most AgTech Robotics Startups Fail — Lessons from Dozens of Failed Companies link.medium.com/F7kX2Al2xQb
🚀 Want to truly understand SLAM with EKF? This complete tutorial on Simultaneous Localization and Mapping takes you step by step through implementation—from theory to a working system. 💡 I’ll guide you through manual calculations at every stage, so you don’t just follow the…
Filter-based SLAM (e.g., EKF) is all about balance: predicting the robot's next state using motion models and correcting it with real-time sensor data. A perfect harmony of prediction and observation. 🚀🤖 Read more: simultaneouslocalizationmapping.com #Robotics #SLAM #EKF
🎯Start with the Base for SLAM - Part 4! Free tutorial to learn how to build a SLAM with EKF for a differential drive robot. The complete tutorial: simultaneouslocalizationmapping.com/slam-with-ekf/ #slam #Robotics #autonomousrobotics
🎯Start with the Base for SLAM - Part 3! Free tutorial to learn how to build a Kalman Filter for a mobile robot. 🔍Discover step by step: ➡️What does the Kalman filter do? ➡️Practical application of Kalman filter. The complete tutorial: simultaneouslocalizationmapping.com/kalman-filter/ #slam #Robotics…
🎯Start with the Base for SLAM - Part 2! Free tutorial to learn how to build a measurement model for a mobile robot. 🔍Discover step by step: ➡️What is a measurement model? ➡️How to use external measurements to correct predictions? The complete tutorial: simultaneouslocalizationmapping.com/measurement-mo…
🎯Start with the Base for SLAM! Learn how to build a motion model for a mobile robot. 🔍Discover step by step: ➡️What is a motion model? ➡️How do you transform sensor data into precise positions? The complete tutorial: simultaneouslocalizationmapping.com/motion-model #robotics #SLAM #autonomousrobot
In an orchard, a farming robot navigate between trees, tending to the soil, while a drone hovers above. Innovation meets nature. #drone #agbot #autonomous #robotics
Innovation in Agriculture RoboFarmer – an autonomous orchard maintenance robot. It is equipped with a tool designed to cut grass between rows. #robotics #agbot #autonomousrobot #ros #gpsrtk
Testing the motors for a 4WD autonomous robot #robotics #agbot #autonomousrobot #4wdrobot
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