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Found 4 papers, 3 papers with code
Online Action Recognition for Human Risk Prediction with Anticipated Haptic Alert via Wearables
This paper proposes a framework that combines online human state estimation, action recognition and motion prediction to enable early assessment and prevention of worker biomechanical risk during lifting tasks.
On the Emergence of Whole-body Strategies from Humanoid Robot Push-recovery Learning
Balancing and push-recovery are essential capabilities enabling humanoid robots to solve complex locomotion tasks.
Gym-Ignition: Reproducible Robotic Simulations for Reinforcement Learning
It interfaces with the new generation of Gazebo, part of the Ignition Robotics suite, which provides three main improvements for reinforcement learning applications compared to the alternatives: 1) the modular architecture enables using the simulator as a C++ library, simplifying the interconnection with external software; 2) multiple physics and rendering engines are supported as plugins, simplifying their selection during the execution; 3) the new distributed simulation capability allows simulating complex scenarios while sharing the load on multiple workers and machines.
A Benchmarking of DCM Based Architectures for Position and Velocity Controlled Walking of Humanoid Robots
More precisely, we present and compare several DCM based implementations of a three layer control architecture.
Robotics
