Embedding and generation of indoor climbing routes with variational autoencoder
Recent increase in popularity of indoor climbing allows possible applications of deep learning algorthms to classify and generate climbing routes. In this work, we employ a variational autoencoder to climbing routes in a standardized training apparatus MoonBoard, a well-known training tool within the climbing community. By sampling the encoded latent space, it is observed that the algorithm can generate high quality climbing routes. 22 generated problems are uploaded to the Moonboard app for user review. This algorithm could serve as a first step to facilitate indoor climbing route setting.
Code (0)
등록된 구현이 없습니다.
Methods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Recurrent Neural Network for MoonBoard Climbing Route Classification and Generation
Classifying the difficulties of climbing routes and generating new routes are both challenging. Existing machine learning models not only fail to accurately predict a problem's difficulty, but they are also unable to gen…
BIG-bench Machine LearningClassificationGeneral ClassificationTransfer LearningClimbing Routes Clustering Using Energy-Efficient Accelerometers Attached to the Quickdraws
One of the challenges for climbing gyms is to find out popular routes for the climbers to improve their services and optimally use their infrastructure. This problem must be addressed preserving both the privacy and conv…
ClusteringTraining and Simulation of Quadrupedal Robot in Adaptive Stair Climbing for Indoor Firefighting: An End-to-End Reinforcement Learning Approach
Quadruped robots are used for primary searches during the early stages of indoor fires. A typical primary search involves quickly and thoroughly looking for victims under hazardous conditions and monitoring flammable mat…
Reinforcement LearningHelpful DoggyBot: Open-World Object Fetching using Legged Robots and Vision-Language Models
Learning-based methods have achieved strong performance for quadrupedal locomotion. However, several challenges prevent quadrupeds from learning helpful indoor skills that require interaction with environments and humans…
Lowering Detection in Sport Climbing Based on Orientation of the Sensor Enhanced Quickdraw
Tracking climbers' activity to improve services and make the best use of their infrastructure is a concern for climbing gyms. Each climbing session must be analyzed from beginning till lowering of the climber. Therefore,…