Characterization of advanced algorithms for autonomous navigation – SLAM 2D-3D. Characterization of trajectories and performance evaluation of autonomous navigation systems

This service evaluates and benchmarks advanced AI-based algorithms for autonomous navigation, enabling companies to improve reliability, safety, and efficiency in robotic and autonomous systems. It supports developers in selecting, validating, and optimising navigation strategies before real-world deployment.

The service assesses algorithm performance using structured test batteries and measurable indicators such as navigation accuracy, obstacle avoidance success rate, trajectory efficiency, response time, and robustness under dynamic conditions. This allows companies to identify strengths, limitations, and improvement opportunities in their solutions.

Two evaluation approaches are considered:

• Use of real machines or robotic platforms: testing is carried out using existing platforms available in the TEF or provided by the customer. This enables validation under real operating conditions, including interaction with sensors, actuators, and physical environments.
• Use of synthetic environments: advanced simulation tools provide virtual environments to evaluate, design, and optimise navigation strategies. These environments allow users to simulate complex robotic systems, including robots, sensors, and their interaction with dynamic and uncertain environments, reducing testing costs and risks.

The service follows a structured process:

• Definition of the navigation use case and performance requirements
• Selection of key performance indicators (KPIs)
• Integration of customer algorithms into testing platforms or simulation environments
• Execution of test scenarios (real and/or virtual)
• Analysis and benchmarking of results
• Recommendations for optimisation and deployment

The result is a detailed technical report describing algorithm performance based on predefined indicators, including quantitative metrics and benchmarking results. Outcomes may include improvements in navigation accuracy, reduction in collision rates, optimisation of path planning, and enhanced system robustness.

Typical applications include autonomous mobile robots (AMRs) in logistics, automated guided vehicles (AGVs) in industrial environments, service robots, and autonomous inspection systems. For example, robotics developers can improve navigation performance in warehouse environments, while technology providers can validate new perception and planning algorithms before integration.

To carry out the service, customers are expected to provide access to their navigation algorithms, system interfaces (e.g. control software, sensor configurations), and, where applicable, robotic platforms or representative datasets. ITA provides testing infrastructure, simulation environments, and expertise in robotics, AI, and autonomous systems.

This service is designed for:

• Robotics and autonomous systems developers seeking to validate and optimise navigation algorithms (e.g. AMR/AGV developers, drone technology companies, service robotics providers)
• Technology companies developing AI-based perception and navigation solutions for industrial or service applications

To start a project, companies can contact ITA to define the use case, available resources, and evaluation scope. This initial step includes a feasibility assessment and KPI definition, followed by a tailored proposal, testing phase, and delivery of results.