Browsing: Robotics
In robotics, natural language is an accessible interface for guiding robots, potentially empowering individuals with limited training to direct behaviors, express preferences, and offer feedback. Recent…
Numerous challenges underlying human-robot interaction exist. One such challenge is enabling robots to display human-like expressive behaviors. Traditional rule-based methods need more scalability in new social…
Robotics is currently exploring how to enhance complex control tasks, such as manipulating objects or handling deformable materials. This research niche is crucial as it promises…
The problem of achieving superior performance in robotic task planning has been addressed by researchers from Tsinghua University, Shanghai Artificial Intelligence Laboratory, and Shanghai Qi Zhi…
The problem of sparsity and degeneracy issues in LiDAR SLAM has been addressed by introducing Quatro++, a robust global registration framework developed by researchers from the…
Researchers from MIT and Meta AI have developed an object reorientation controller that can utilize a single depth camera to reorient diverse shapes of objects in…
Training robots to perform various manipulation behaviors has been made possible by imitation learning from human demonstrations. One popular method involves having human operators teleoperate with…
In many domains that involve machine learning, a widely successful paradigm for learning task-specific models is to first pre-train a general-purpose model from an existing diverse…
Teaching robots complicated manipulation skills through observation of human demonstrations has shown promising results. Providing extensive manipulation demonstrations is time-consuming and labor costly, making it challenging…
With the increase in the popularity and use cases of Artificial Intelligence, Imitation learning (IL) has shown to be a successful technique for teaching neural network-based…