Learning-based legged locomotion: State of the art and future perspectives
S Ha, J Lee, M van de Panne, Z ** is the next frontier in rl
Many roboticists dream of presenting a robot with a task in the evening and returning the
next morning to find the robot capable of solving the task. What is preventing us from …
next morning to find the robot capable of solving the task. What is preventing us from …
The future of the labor force: higher cognition and more skills
W Zhang, KH Lai, Q Gong - Humanities and Social Sciences …, 2024 - nature.com
Skills can be categorized into two types: social-cognitive and sensory-physical. Sensory-
physical skills, governed by explicit rules and transparent rationales, can be effectively …
physical skills, governed by explicit rules and transparent rationales, can be effectively …
Efficient Tactile Sensing-based Learning from Limited Real-world Demonstrations for Dual-arm Fine Pinch-Grasp Skills
Imitation learning for robot dexterous manipulation, especially with a real robot setup,
typically requires a large number of demonstrations. In this paper, we present a data-efficient …
typically requires a large number of demonstrations. In this paper, we present a data-efficient …
Masked Sensory-Temporal Attention for Sensor Generalization in Quadruped Locomotion
With the rising focus on quadrupeds, a generalized policy capable of handling different robot
models and sensory inputs will be highly beneficial. Although several methods have been …
models and sensory inputs will be highly beneficial. Although several methods have been …
An advanced reinforcement learning control method for quadruped robots in typical urban terrains
C Yan, N Wang, H Gao, X Wang, C Tang… - International Journal of …, 2024 - Springer
Quadruped robots, with their exceptional flexibility and stable structure, are highly suitable
for traversing the complex unstructured terrains in urban environments. However, the current …
for traversing the complex unstructured terrains in urban environments. However, the current …
Distilling Reinforcement Learning Policies for Interpretable Robot Locomotion: Gradient Boosting Machines and Symbolic Regression
F Acero, Z Li - arxiv preprint arxiv:2403.14328, 2024 - arxiv.org
Recent advancements in reinforcement learning (RL) have led to remarkable achievements
in robot locomotion capabilities. However, the complexity and``black-box''nature of neural …
in robot locomotion capabilities. However, the complexity and``black-box''nature of neural …
Constrained Skill Discovery: Quadruped Locomotion with Unsupervised Reinforcement Learning
Representation learning and unsupervised skill discovery can allow robots to acquire
diverse and reusable behaviors without the need for task-specific rewards. In this work, we …
diverse and reusable behaviors without the need for task-specific rewards. In this work, we …