Autonomous vehicles for transport of materials in warehouses

Summary of the technology

Based on current SLAM techniques, researchers have developed new algorithms with important improvements in the map creation, association and location processes. In this way, the vehicle reaches a better adaptation to the space and organization of the warehouse. In other words, the vehicle can be adapted to the place and it is not necessary to adapt the place to the vehicle.

The main innovative aspects are:
• The vehicles have a high level of autonomy, due to the dynamic planning of paths.
• Avoid collisions because the system can modify the path in real time.
• The definition of new paths without modification of the environment avoids costly investments.

Universidad de Alicante

Description of the technology

University researchers have developed a low cost device that can be adapted to any kind of vehicles allowing the transport of loads in complex spaces without the need for drivers. This system is ideal for transporting materials in warehouses. This allows for the reconstruction of the area by mapping and pinpointing, and the identification of moving objects and people. It also reckons the optimal path to reach a certain point, avoiding potential obstacles through reinforcement learning techniques.


The automatically guided vehicles (AGV), heretofore used in warehouse management, are based on the use of previously established paths, that is, guided by painted lines or lasers. These systems have a limited flexibility and no ability to solve unforeseen situations, which can lead to hit unexpected objects that hinder the movement of goods and obstruct the passing. Furthermore, the establishment of new routes involves programming prior work with high temporal and economic cost. Another disadvantage is the difficulty of working in places with people on the move, since it can lead to accidents and collisions. The intention is to convert any manually driven vehicle into a high-performed mobile robot to suit the working environment where it is going to operate, rather than having to adapt the environment to the vehicle, with the high cost of doing so. This research work has led to a technology patented by the University of Alicante that improve processes mapping, association and location of robots over SLAM conventional techniques (Simultaneous Localization and Mapping). This technology is applicable to any business or industrial environment where autonomous vehicles can be used, for example, in the management of warehouses with large volume of inputs and outputs, production centers in need of displacing objects between different points, movement of goods in settings with extreme human conditions (cold storage, waste management, etc.). The device is available to be adapted to conventional vehicles, new or used. As a practical demonstration of this technology, a golf cart has been automated and it is currently circulating autonomously on the University of Alicante campus. Also, there is a virtual reality simulator to visualize the application of this technology in specific tasks and facilities of each company. Therefore, the research group has the capacity to automate a fleet of vehicles based on the needs of the company.

Main advantages of its use

  • Continuous learning. It is not required a calibration process. The robotic system is able to learn the vehicle dynamics.
  • Easy adaptation. The system allows to modify the route or to include a new one, easily.
  • Reduced cost. It doesn’t require special vehicles. The equipment needed is reduced and the time to install the system is less than the time required with conventional technologies.
  • The development of new strategies in the SLAM technique allows the achievement of several new advantages with respect other technologies for automatically guided vehicles.
  • The technology can be installed in any conventional vehicle, new or used, without calibration. It can be installed in the vehicle fleet of the company. So these vehicles can operate automatically with the new technology, or manually (driven by a person). This means a reduction of implementation costs.
  • Versatility in trajectory planning. The path is not defined previously. It is only necessary to define the start and end points, and the system is able to identify objects in the surroundings, to adapt the route and determine the optimum path. The system is able to avoid obstacle while circulating too. This allows to install the system in complex environments with several elements on the move.


  • Management of warehouses with continuous passage of goods.
  • Movement of goods in extreme conditions for person (cold storage, waste management, etc.).
  • Production centres where it is necessary to transport materials.
  • The technology is applicable to any industrial environment where industrial vehicles are required.

Additional information (attached documents)

Attached documents

Related Keywords

  • Automation, Robotics Control Systems
  • Imaging, Image Processing, Pattern Recognition
  • Remote Control
  • Applications for Transport and Logistics
  • Logistics
  • Traffic Engineering / Control Systems
  • Manufacturing/industrial
  • Robotics
  • Machine vision software and systems
  • Industrial trucks and tractors
  • Motor vehicles, transportation equipment and parts
  • vehicle
  • transport
  • Warehouse
  • robotics
  • motor
  • Automation
  • remote control
  • logistics
  • traffic.

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