Evaluation of alternative, complementary or improved autonomous navigation strategies for specific use cases – SLAM 2D-3D

This service evaluates and optimises AI-based autonomous navigation strategies, enabling companies to improve accuracy, safety, and efficiency in robotic systems. It supports technology developers in validating navigation algorithms and enhancing their performance before deployment in real operational environments.

The service assesses customer navigation strategies in representative applications such as warehouse automation, industrial logistics, autonomous mobile robots (AMRs), and automated guided vehicles (AGVs). It analyses performance to identify limitations and improvement opportunities, helping companies reduce navigation errors, avoid collisions, and optimise path planning.

Performance evaluation is based on measurable indicators such as navigation accuracy, trajectory efficiency, obstacle avoidance success rate, response time, and robustness under dynamic conditions. These metrics allow companies to quantify improvements in operational efficiency, safety, and system reliability.

The service includes:

• Performance analysis and benchmarking of navigation algorithms
• Validation under real and simulated operating conditions
• Identification of optimisation opportunities
• Proposal and initial evaluation of alternative or complementary solutions (e.g. sensor fusion, AI-based planning, hybrid navigation strategies)

Two evaluation approaches are considered:

• Use of real machines or robotic platforms: testing is carried out using platforms available in the TEF or provided by the customer. This enables validation in real environments, including interaction with sensors, infrastructure, and dynamic obstacles.
• 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 industrial environments, reducing development time and testing costs.

The service follows a structured process:

• Definition of the navigation use case and key performance indicators (KPIs)
• Review of customer algorithms, system architecture, and data inputs
• Integration into testing platforms (real or simulated)
• Execution of test scenarios under controlled and variable conditions
• Analysis and benchmarking of results
• Development and validation of improved solutions

The expected results include a technical report detailing algorithm performance, benchmarking results, and recommendations for optimisation. In addition, where relevant, a pilot validation in a representative environment can be delivered to demonstrate the effectiveness of improved navigation strategies.

Typical applications include optimisation of robotic navigation in warehouses, improvement of AGV routing in manufacturing plants, and validation of autonomous systems in dynamic environments. For example, robotics developers can increase navigation success rates and reduce collision risks, while industrial companies can improve logistics efficiency and reduce operational downtime.

To carry out the service, customers are expected to provide access to their navigation algorithms, relevant datasets (e.g. maps, sensor data such as LiDAR or vision), and system interfaces. Where applicable, robotic platforms or test environments can also be provided by the customer. ITA provides testing infrastructure, simulation environments, and expertise in robotics, AI, and autonomous systems.

This service is designed for:

• Robotics and autonomous systems developers (e.g. AMR/AGV manufacturers, drone technology companies) seeking to validate and optimise navigation strategies
• Technology companies developing AI-based 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, followed by a tailored proposal, execution of testing activities, and delivery of results.