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Related lectures (35)
Computational Robot Design: Co-Optimization Insights
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Explores computational robot design, emphasizing co-optimization insights and the use of graph grammars for efficient design.
Computational Robot Design: Morphological Intelligence and Simulation
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Explores computational robot design, morphological intelligence, simulation, and innovative contact dynamics solutions.
Improving Robot Design: Data-Driven Approaches
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Explores data-driven approaches to improve robot design, focusing on compliance, soft materials, and complex interactions.
Embracing Complexity for Enduring and Adaptive Robots
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Delves into the necessity of complex organ systems in robots to enhance their abilities and lifespan.
Robot Simulation and Programming
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Covers the basics of robot simulation and programming using Webots.
Perceptual Robotics: Integrating Vision and Action
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Covers the integration of visual perception and robotic actions in embodied AI.
Robotics Invention Commercialization
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Explores the journey of an independent inventor in the robotics industry, from patenting to commercializing a new industrial robot technology.
Computational Robot Design: Differentiable Simulation and Control
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Explores optimization-driven design, differentiable simulation, control strategies, and the evolution of virtual creatures and soft machines.
Active Map Building: Exploration
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Explores the basics of Simultaneous Localization and Mapping (SLAM), focusing on map creation techniques and prediction of measurements.
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Haptic Teleoperation: Ocean Exploration and Robot Manipulation
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Explores haptic teleoperation for ocean exploration, robot manipulation, and entertainment applications.
Collaborative Robots: Mechanical Systems
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Covers collaborative robots, bolted assemblies, prestressing, and screw stiffness in mechanical systems.
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Neural Architectures for Embodied AI and Cognition
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Explores neural architectures for embodied AI, cognitive systems, and the integration of computing and robotics.
Neural Networks: Logic and Applications
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Explores the logic of neuronal function, the Perceptron model, deep learning applications, and levels of abstraction in neural models.
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