Baidu Research Robotics and Auto-Driving Lab (RAL) and the University of Maryland, College Park, developed an autonomous excavator system (AES) that can perform material loading tasks without any human intervention. The developers claim the system offers performance close to that of an experienced human operator.
AES uses real-time algorithms for perception, planning, and control alongside a new architecture for autonomous operation. Multiple sensors – including LiDAR, cameras, and proprioceptive sensors – are integrated for the perception module to perceive the 3D environment and identify target materials, along with advanced algorithms such as a dedusting neural network to generate clean images. With this modular design, the AES architecture can be used by excavators of all sizes.
To evaluate AES, researchers teamed up with a leading equipment manufacturing company to deploy the system at a waste disposal site, a toxic and harmful real-world scenario where automation is in strong demand. Despite the challenging assignment, AES was able to continuously operate for more than 24 hours without any human intervention.
AES has also been tested in winter weather conditions, where vaporization can pose a threat towards the sensing performance of LiDAR. The amount of materials excavated, in both wet and dry form, was 67.1 cubic meters per hour for a compact excavator, which is in line with the performance of a traditional human operator.
“AES performs consistently and reliably over a long time, while the performance of human operators can be uncertain,” said Dr. Liangjun Zhang, corresponding author and the head of Baidu Research Robotics and Auto-Driving Lab.
Going forward, Baidu Research RAL will continue to refine core modules of AES and further explore scenarios where extreme weather or environmental conditions may be present. The researchers described their methodology in a research paper published in Science Robotics.
“This work presents an efficient, robust, and general autonomous system architecture that enables excavators of various sizes to perform material loading tasks in the real world autonomously,” said Dr. Liangjun Zhang, corresponding author and the Head of Baidu Research Robotics and Auto-Driving Lab.
Excavators are vital for infrastructure construction, mining, and rescue applications. The global market size for excavators was $44.12 billion in 2018 and is expected to grow to $63.14 billion by 2026.
Baidu has been collaborating with several of the world’s leading construction machinery companies to automate traditional heavy construction machinery with AES. “We aim to leverage our robust and secure platform, infused with our powerful AI and cloud capabilities to transform the construction industry,” said Dr. Haifeng Wang, CTO of Baidu.
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