16 citations · 61 across the 31 of their papers we have counts for
34 papers
Path Signatures for Diversity in Probabilistic Trajectory Optimisation
Lucas Barcelos, Tin Lai, Rafael Oliveira +2
Motion planning can be cast as a trajectory optimisation problem where a cost is minimised as a function of the trajectory being generated. In complex environments with several obs…
Learning to Simulate Tree-Branch Dynamics for Manipulation
Jayadeep Jacob, Tirthankar Bandyopadhyay, Jason Williams +2
We propose to use a simulation driven inverse inference approach to model the dynamics of tree branches under manipulation. Learning branch dynamics and gaining the ability to mani…
IndustReal: Transferring Contact-Rich Assembly Tasks from Simulation to Reality
Bingjie Tang, Michael A. Lin, Iretiayo Akinola +5
Robotic assembly is a longstanding challenge, requiring contact-rich interaction and high precision and accuracy. Many applications also require adaptivity to diverse parts, poses,…
DefGraspNets: Grasp Planning on 3D Fields with Graph Neural Nets
Isabella Huang, Yashraj Narang, Ruzena Bajcsy +3
Robotic grasping of 3D deformable objects is critical for real-world applications such as food handling and robotic surgery. Unlike rigid and articulated objects, 3D deformable obj…
Batch Bayesian optimisation via density-ratio estimation with guarantees
Rafael Oliveira, Louis Tiao, Fabio Ramos
Bayesian optimisation (BO) algorithms have shown remarkable success in applications involving expensive black-box functions. Traditionally BO has been set as a sequential decision-…
Renaissance Robot: Optimal Transport Policy Fusion for Learning Diverse Skills
Julia Tan, Ransalu Senanayake, Fabio Ramos
Deep reinforcement learning (RL) is a promising approach to solving complex robotics problems. However, the process of learning through trial-and-error interactions is often highly…