José António Bernardo, R&D project manager at ABMI Groupe, discusses the transition from laboratory to real-world applications in robotics, AI, and embedded systems. He emphasizes that a robot's performance is not defined by demonstration quality but by its reliability, repeatability, and safety in real-world conditions.
Bernardo highlights the significance of Physical AI and adaptive robots, noting that the convergence of AI, embedded systems, and robotics is crucial for success. He shares a specific example where a positioning function showed a 24 mm error, which was corrected to 1.8 mm through their own inverse kinematics, illustrating the importance of accurate measurement and validation.
Looking ahead, Bernardo points out that the main challenges lie in data and validation methods. He stresses that without a way to prove a system's functionality outside its training domain, the industry risks producing mere demonstrations rather than viable products. The conversation underscores the need for robust validation processes to ensure industrial robots can operate effectively in dynamic environments.
Editor's Note
The insights from José António Bernardo reflect critical challenges in the robotics industry, particularly regarding the integration of AI and embedded systems. As companies strive for reliable and adaptable robotic solutions, the focus on validation and real-world performance becomes increasingly vital. This highlights the importance of developing robust methodologies to bridge the gap between simulation and practical application.
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