ROS 2 Sensor Fusion and Autonomous Navigation — From Sensors to Maps
Master the art of high-performance robotics. Integrate IMU, LiDAR, and cameras to build robust navigation stacks and SLAM pipelines using modern ROS 2 protocols.
Secure Your Spot
Register now to attend the upcoming live interactive Bootcamp.
About this Bootcamp
This intensive Bootcamp is engineered for robotics software engineers and system integrators who need to bridge the gap between raw sensor data and intelligent autonomous movement. Moving beyond basic tutorials, we dive deep into the ROS 2 Humble/Iron ecosystem, focusing on the real-world complexities of TF frames, sensor fusion, and mapping algorithms. Through live demonstrations and hands-on node construction, you will learn to manage low-latency data paths and deploy a working navigation stack.
What You Will Learn
- check_circle Linux for Robotics Mastery: Optimize workspaces and manage the lifecycle of ROS 2 nodes for mission-critical applications.
- check_circle Sensor Driver Integration: Master URDF/XACRO configuration and manage complex TF transforms for LiDAR and Cameras.
- check_circle Advanced Localization & SLAM: Implement particle filters and graph-based SLAM to create high-fidelity maps in dynamic environments.
- check_circle Real-Time Navigation Stacks: Configure path planning and obstacle avoidance using fused sensor data for autonomous mobile robots.
Bootcamp Outcomes
By the end of this session, you will possess a battle-tested ROS 2 node pattern for multi-sensor fusion and a functional localization/mapping pipeline prototype ready for deployment on physical or simulated robot hardware.
Intensive 3-Hour Agenda
A structured roadmap from environment setup to autonomous navigation
ROS 2 Foundations & Core Environment
Environment setup, workspace management, and defining the robot's physical description using URDF and XACRO.
Sensor Integration & TF Management
Connecting LiDAR, IMU, and Cameras; managing coordinate transforms (TF) and ensuring low-latency data paths.
Sensor Fusion & SLAM Fundamentals
Deep dive into Kalman filters and SLAM algorithms to synchronize disparate sensor feeds into a unified map.
Autonomous Navigation Lab
Hands-on build of a localization flow and path-planning pipeline, followed by an integration checklist for deployment.
What Industry Demands
The skills required by top-tier robotics firms like Amazon Robotics, Waymo, and Tesla
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ROS 2 Proficiency
Companies are migrating to ROS 2 for its security and real-time capabilities.
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Robust Perception
Reliable sensor fusion is mandatory to ensure robots can navigate noisy, real-world environments.
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Hardware-Software Sync
The ability to integrate middleware with low-level Linux kernels for deterministic robot behavior.
What Participants Say
"The focus on TF management and sensor fusion was exactly what I needed. The hands-on nodes were production-ready."
Sarah Jenkins
Perception Engineer at Autonomous Systems"Most tutorials ignore real-time Linux tuning. This bootcamp treated robotics as the high-stakes engineering field it is."
Marcus Thorne
Robotics Software Developer"Finally, a clear explanation of SLAM basics that actually leads to a working navigation stack in ROS 2."
Amit Kumar
Systems IntegratorUpcoming Bootcamp Sessions
LIVE SESSION
ROS 2 Sensor Fusion Cohort A
LIVE SESSION
ROS 2 Sensor Fusion Cohort B
LIVE SESSION
ROS 2 Sensor Fusion Cohort C
Why Join
Pantech Bootcamps