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Training SLAM and Sensor Fusion - Optimizing Autonomous Navigation

Course created on July 27, 2026Updated on October 5, 2026

On quote$5,775

5 days
Onsite
10 people max.

Request a quote See the program

Ref: OTK907

10 people max.

On quote$5,775

In-company rate: on quotefrom $10,395 for the whole team

On-site and certification exam on quote

5 days

Onsite

Don't let this gap widen

Why this program matters

Companies that fail to master SLAM and sensor fusion lose 35% accuracy in autonomous navigation according to recent industry studies.
This gap causes delays in IoT project deliveries and a 22% increase in maintenance costs.
Engineers without these skills see their employability stall against international competition.
Not investing in this training exposes the organization to lasting technological lag and loss of competitiveness in the robotics and intelligent systems markets.

Trusted by — schools, companies and industrial groups

25,750 programs · 25 countries

Every program built with a dedicated engineer

Companies: Aptar, ArcelorMittal, Equans, EDF, Ubisoft and Microsoft.

Learning objectives

Master advanced SLAM algorithms for professional IoT applications
Develop skills in multi-modal sensor fusion in a business context
Design certifiable and robust real-time localization architectures
Implement optimized Sensor Fusion solutions for industrial environments
Optimize the performance of autonomous mapping systems through practical training
Deploy complete SLAM projects tailored to the company's business needs

Program

Module 1Theme: Advanced Fundamentals of SLAM and Sensor Fusion (ROS2, Kalman, Industrial Cases)

Participants explore the mathematical foundations of SLAM and sensor fusion through concrete exercises in ROS2. They analyze real datasets, configure extended Kalman filters, and produce an initial basic localization deliverable on a simulated IoT platform.

Module 2Theme: Visual-Inertial SLAM and Sensor Calibration (OpenCV, IMU, Calibration Toolbox)

This day is dedicated to integrating cameras and inertial measurement units. Learners perform multi-sensor calibration exercises, implement VIO algorithms, and validate their results on autonomous navigation scenarios in indoor environments.

Module 3Theme: Multi-Sensor SLAM and Graph Optimization (GTSAM, Factor Graphs, Real Datasets)

Professionals build factor graphs to fuse LiDAR, cameras, and odometry. They optimize trajectories on industrial data, compare multiple solvers, and deliver a precise 3D map with quantified performance metrics.

Module 4Theme: Real-Time SLAM and Robustness (Loop Closure, Relocalization, Edge Computing)

Focus on real-time execution and failure management. Participants integrate loop closure mechanisms, test relocalization on existing maps, and deploy an optimized solution on an edge IoT platform with resource monitoring.

Module 5Theme: SLAM and Sensor Fusion in Production (Docker, MQTT, Final Project Evaluation)

Synthesis and production deployment day. Each participant finalizes their SLAM project, integrates MQTT communication, containerizes their application, and presents results to the group. Complete deliverables and technical report submitted at the end of the training.

Evaluation method

Daily technical quizzes on SLAM and fusion concepts
Practical project evaluated continuously with daily deliverables
Final presentation of the IoT use case and group debrief

Learning method

Access to a remote practical work platform 24/7 for 3 months
Educational resources and source codes provided in advance
Weekly Q&A sessions post-training
Skills certification awarded after project validation

Methods, materials and delivery

The Training SLAM and Sensor Fusion - Optimizing Autonomous Navigation program is delivered onsite or remote (blended-learning, virtual classroom, remote presence). At Learni, an industry-certified training organization, every program is built to maximize skills acquisition regardless of the chosen format.

The trainer alternates between demonstrative, interrogative and active methods (through hands-on labs and/or scenarios). This pedagogical approach guarantees concrete learning that's immediately applicable at work.

Equipment required

For the smooth delivery of the Training SLAM and Sensor Fusion - Optimizing Autonomous Navigation program, the following equipment is required:

Mac or PC computers, high-speed fiber internet, whiteboard or flipchart, projector or interactive touch screen (for remote sessions)
Training environments installed on workstations or accessible online
Course materials, hands-on exercises and complementary resources
Post-training access to materials and educational resources

For intra-company training on a site outside Learni, the client commits to providing all required teaching materials (computers, internet, etc.) for the smooth delivery of the program in line with the prerequisites in the communicated program.

* contact us for remote delivery feasibility** ratio varies depending on the program

Skills assessment methods

Assessment of skills acquired during the Training SLAM and Sensor Fusion - Optimizing Autonomous Navigation program is performed through:

During training: case studies, hands-on labs and professional scenarios
End of training: self-assessment questionnaire and skills evaluation by the trainer
After training: completion certificate detailing acquired skills

Program accessibility

Learni is committed to making its programs accessible. All our programs are accessible to people with disabilities. Our teams are available to adapt the pedagogical methods to your specific needs. Please contact us for any adjustment request.

Enrollment terms and lead times

Registration is possible up to 48 business hours before the start of training. All our programs are built for corporate L&D budgets and delivered onsite or remotely.

The Learni story

Founded by engineers and learning experts, Learni's mission is to make high-impact tech training accessible to teams everywhere. We work remotely with organizations across the US and Canada, in your time zone, to help teams upskill fast.

Our method

Training quality, guaranteed at every step

Before, during, after: we frame the brief, introduce the trainer, tailor the content and measure impact. You stay in control from kickoff to wrap-up.

Step 1

Rigorous trainer selection

Each trainer is validated on three criteria: hands-on field expertise, proven pedagogy and alignment with your industry.

Triple validation: technical, pedagogical, sectoral.
Minimum rating 4.8/5 over the last 12 sessions.

Step 2

You meet the trainer beforehand

30-minute video call between you and the selected trainer to validate the fit, adjust content and clear any final doubts.

Live briefing on goals and team context.
Veto right — we swap the trainer for free if needed.

Step 3

Content tailored to your context

No recycled slides. The syllabus is reworked from your real cases: tools, constraints, vocabulary, ongoing projects.

Hands-on cases drawn from your stack and projects.
Program co-written then validated by your team.

Step 4

Continuous quality follow-up

Live evaluations, 30/90/180-day check-ins and a consolidation plan. If the impact misses the mark, we rework it.

NPS, knowledge quizzes and skills self-assessment.
Satisfaction guarantee: fully satisfied or free rework.

A simple promise: you don't pay to discover the trainer on day one. Everything is validated upfront, by you.

A child walking to school with a backpack

Our social commitment

A school kit donated to a child for every training booked

To fight inequalities in access to education, Learni donates a complete school kit to a child in need for every training booked. You build your skills, a child heads back to school.

Backpack, notebooks and essential supplies
Distributed through our partner charities
Included, at no extra cost to you

Enroll and offer a kit

FAQ

Frequently asked questions

Which tools are used in SLAM and Sensor Fusion training?+

Hands-on work runs on ROS2, kalman, industrial Cases, openCV, IMU and calibration Toolbox. Those tools come from the SLAM and Sensor Fusion program itself, delivered on site over 5 days, so participants practise on the stack they will use at work.

What can participants do after SLAM and Sensor Fusion training?+

They can master advanced SLAM algorithms for professional IoT applications, develop skills in multi-modal sensor fusion in a business context and design certifiable and robust real-time localization architectures. Those are the stated objectives of the SLAM and Sensor Fusion program at Advanced level, checked by the end-of-session assessment.

What does the SLAM and Sensor Fusion program cover, day by day?+

Day 1: Theme: Advanced Fundamentals of SLAM and Sensor Fusion (ROS2, Kalman, Industrial Cases). Day 2: Theme: Visual-Inertial SLAM and Sensor Calibration (OpenCV, IMU, Calibration Toolbox). Day 3: Theme: Multi-Sensor SLAM and Graph Optimization (GTSAM, Factor Graphs, Real Datasets). Day 4: Theme: Real-Time SLAM and Robustness (Loop Closure, Relocalization, Edge Computing). Day 5: Theme: SLAM and Sensor Fusion in Production (Docker, MQTT, Final Project Evaluation). The SLAM and Sensor Fusion program runs over 5 days, delivered on site.

How is SLAM and Sensor Fusion training assessed?+

Assessment relies on daily technical quizzes on SLAM and fusion concepts, practical project evaluated continuously with daily deliverables and final presentation of the IoT use case and group debrief. Learni issues a completion certificate together with the individual assessment report at the end of the SLAM and Sensor Fusion program, which an L&D team can file as evidence.

How much does SLAM and Sensor Fusion training cost per participant?+

SLAM and Sensor Fusion training is priced on quote. The amount depends on headcount, format and how far the syllabus is tailored to your team. A detailed quote is sent within one business day, and team pricing covers the whole group from the second participant.SLAM and Sensor Fusion training costs $5,775 per participant. For an in-company team, the flat rate starts at $10,395 for the whole group, up to 8 people. The detailed quote, sent within one business day, adjusts the amount to the format and how far the syllabus is tailored to your team.

How long does SLAM and Sensor Fusion training take?+

5 days, available live online (US time zones) or on-site at your offices. Half-day tracks spread over several weeks are possible so the team stays operational.

Who pays for SLAM and Sensor Fusion training?+

Most US teams pay directly through their company L&D or training budget. Learni invoices in US dollars and accepts bank transfer (ACH/wire) or card, with volume pricing for teams. A purchase order is welcome.

What do participants need to know before SLAM and Sensor Fusion training?+

Proficiency in Python, solid foundations in linear algebra, prior experience with ROS2 and industrial sensors.

Is a certificate issued after SLAM and Sensor Fusion training?+

Yes. A Learni completion certificate is issued, along with the individual evaluation report. Learni is a certified training provider and prepares for third-party certifications, but does not award them itself.

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