Altair Case Studies Optimizing Robotic Car Storage Service: A Stanley Robotics Case Study

	Optimizing Robotic Car Storage Service: A Stanley Robotics Case Study Altair

Optimizing Robotic Car Storage Service: A Stanley Robotics Case Study

Altair

Technology Category	Robots - Autonomous Guided Vehicles (AGV) Sensors - Autonomous Driving Sensors
Applicable Industries	Automotive Transportation
Applicable Functions	Logistics & Transportation Maintenance
Use Cases	Autonomous Robots Digital Twin
Challenge	Stanley Robotics, a deep tech company, aimed to revolutionize the vehicle logistics industry by introducing autonomous robots to move cars in storage compounds. The challenge was to develop a robot that was fast, reliable, and efficient to meet the demands of the car logistics industry. The robot needed to be designed with mechanical optimization in mind to compete effectively with traditional car logistics companies. Stanley Robotics needed to prove that its robotic vehicle could achieve a significant number of moves per year and demonstrate its durability. To achieve this, the company needed a partner to help develop a digital twin of their robot to calculate all the demands placed upon it and validate their product through durability calculations. Read More
About Customer	Stanley Robotics is a deep tech company founded in 2015 by Clement Boussard and Aurélien Cord. The company's original idea was to move cars via an intelligent robot instead of automating the cars and giving them the ability to park themselves. After analyzing the market for long-duration parking in airports, Stanley Robotics realized its product was perfect for the car logistics industry. Their outdoor robots can move cars up to 2600kg and deposit them to their parking slot with the help of a central intelligence hub that manages the fleet, cars, and parking activities. Read More
Solution	Stanley Robotics partnered with Altair, an engineering simulation software supplier. They used Altair's Inspire Motion to enable the robot multi-body model to be used for pre-sizing. The model was further enhanced with Altair's MotionSolve to enable advanced functions, including performing 3D road definition, longitudinal and lateral tire forces (to simulate handling and durability), and dedicated simulation scenarios. The Stanley team refined the model by representing key components as flexible bodies to capture the deformations and vibrations of the robot’s chassis when exposed to standardized vehicle durability events. With the complete CAE process in place, it became possible to investigate the robot’s sensitivity and robustness, and to identify optimal design characteristics. Read More Log in to view content
Contents

Technology Category

Robots - Autonomous Guided Vehicles (AGV)

Sensors - Autonomous Driving Sensors

Applicable Industries

Automotive

Transportation

Applicable Functions

Logistics & Transportation

Maintenance

Use Cases

Autonomous Robots

Digital Twin

Challenge

Stanley Robotics, a deep tech company, aimed to revolutionize the vehicle logistics industry by introducing autonomous robots to move cars in storage compounds. The challenge was to develop a robot that was fast, reliable, and efficient to meet the demands of the car logistics industry. The robot needed to be designed with mechanical optimization in mind to compete effectively with traditional car logistics companies. Stanley Robotics needed to prove that its robotic vehicle could achieve a significant number of moves per year and demonstrate its durability. To achieve this, the company needed a partner to help develop a digital twin of their robot to calculate all the demands placed upon it and validate their product through durability calculations.

About Customer

Stanley Robotics is a deep tech company founded in 2015 by Clement Boussard and Aurélien Cord. The company's original idea was to move cars via an intelligent robot instead of automating the cars and giving them the ability to park themselves. After analyzing the market for long-duration parking in airports, Stanley Robotics realized its product was perfect for the car logistics industry. Their outdoor robots can move cars up to 2600kg and deposit them to their parking slot with the help of a central intelligence hub that manages the fleet, cars, and parking activities.

Solution

Stanley Robotics partnered with Altair, an engineering simulation software supplier. They used Altair's Inspire Motion to enable the robot multi-body model to be used for pre-sizing. The model was further enhanced with Altair's MotionSolve to enable advanced functions, including performing 3D road definition, longitudinal and lateral tire forces (to simulate handling and durability), and dedicated simulation scenarios. The Stanley team refined the model by representing key components as flexible bodies to capture the deformations and vibrations of the robot’s chassis when exposed to standardized vehicle durability events. With the complete CAE process in place, it became possible to investigate the robot’s sensitivity and robustness, and to identify optimal design characteristics.

Impact #1	The partnership with Altair enabled Stanley Robotics to achieve its two key objectives. The company developed a digital twin that allows it to understand its product better and significantly reduced computation time. Leveraging this digital twin and Altair’s solutions, Stanley Robotics can now validate its robotic vehicle’s parts and systems quicker and more efficiently. The virtual validation process allows the company to design its robotic vehicle with less mass and lower production and maintenance costs. It also encourages innovation as designers can try new, experimental design characteristics while ensuring all robots meet durability standards. As a result, Stanley Robotics can meet and exceed the expectations of the car logistics industry.

Impact #1

The partnership with Altair enabled Stanley Robotics to achieve its two key objectives. The company developed a digital twin that allows it to understand its product better and significantly reduced computation time. Leveraging this digital twin and Altair’s solutions, Stanley Robotics can now validate its robotic vehicle’s parts and systems quicker and more efficiently. The virtual validation process allows the company to design its robotic vehicle with less mass and lower production and maintenance costs. It also encourages innovation as designers can try new, experimental design characteristics while ensuring all robots meet durability standards. As a result, Stanley Robotics can meet and exceed the expectations of the car logistics industry.

Benefit #1	Reduced mechanical part mass by up to 30%
Benefit #2	Reduced mechanical part cost by up to 20%
Benefit #3	Ensured 10-year service life standard

Benefit #1

Reduced mechanical part mass by up to 30%

Benefit #2

Reduced mechanical part cost by up to 20%

Benefit #3

Ensured 10-year service life standard

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Overview

Optimizing Robotic Car Storage Service: A Stanley Robotics Case Study

Operational Impact

Quantitative Benefit