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Insect-inspired AI for autonomous robots
Autonomous robots are expected to perform a wide range of sophisticated tasks in complex,
unknown environments. However, available onboard computing capabilities and algorithms …
unknown environments. However, available onboard computing capabilities and algorithms …
Control of human gait stability through foot placement
During human walking, the centre of mass (CoM) is outside the base of support for most of
the time, which poses a challenge to stabilizing the gait pattern. Nevertheless, most of us are …
the time, which poses a challenge to stabilizing the gait pattern. Nevertheless, most of us are …
Caterpillar-inspired soft crawling robot with distributed programmable thermal actuation
Many inspirations for soft robotics are from the natural world, such as octopuses, snakes,
and caterpillars. Here, we report a caterpillar-inspired, energy-efficient crawling robot with …
and caterpillars. Here, we report a caterpillar-inspired, energy-efficient crawling robot with …
Real-world humanoid locomotion with reinforcement learning
I Radosavovic, T ** and perching in arboreal environments
Birds take off and land on a wide range of complex surfaces. In contrast, current robots are
limited in their ability to dynamically grasp irregular objects. Leveraging recent findings on …
limited in their ability to dynamically grasp irregular objects. Leveraging recent findings on …
Human-in-the-loop optimization of exoskeleton assistance during walking
Exoskeletons and active prostheses promise to enhance human mobility, but few have
succeeded. Optimizing device characteristics on the basis of measured human performance …
succeeded. Optimizing device characteristics on the basis of measured human performance …
Multi-receptor skin with highly sensitive tele-perception somatosensory
The limitations and complexity of traditional noncontact sensors in terms of sensitivity and
threshold settings pose great challenges to extend the traditional five human senses. Here …
threshold settings pose great challenges to extend the traditional five human senses. Here …
Verifiable reinforcement learning via policy extraction
While deep reinforcement learning has successfully solved many challenging control tasks,
its real-world applicability has been limited by the inability to ensure the safety of learned …
its real-world applicability has been limited by the inability to ensure the safety of learned …