6 papers
KinDER: A Physical Reasoning Benchmark for Robot Learning and Planning
Yixuan Huang, Bowen Li, Vaibhav Saxena +9
Robotic systems that interact with the physical world must reason about kinematic and dynamic constraints imposed by their own embodiment, their environment, and the task at hand.…
Aug3D: Augmenting large scale outdoor datasets for Generalizable Novel View Synthesis
Aditya Rauniyar, Omar Alama, Silong Yong +2
Recent photorealistic Novel View Synthesis (NVS) advances have increasingly gained attention. However, these approaches remain constrained to small indoor scenes. While optimizatio…
CoCap: Coordinated motion Capture for multi-actor scenes in outdoor environments
Aditya Rauniyar, Micah Corah, Sebastian Scherer
Motion capture has become increasingly important, not only in computer animation but also in emerging fields like the virtual reality, bioinformatics, and humanoid training. Captur…
Multi-Robot Planning for Filming Groups of Moving Actors Leveraging Submodularity and Pixel Density
Skyler Hughes, Rebecca Martin, Micah Corah +1
Observing and filming a group of moving actors with a team of aerial robots is a challenging problem that combines elements of multi-robot coordination, coverage, and view planning…
Enhancing Multi-Drone Coordination for Filming Group Behaviours in Dynamic Environments
Aditya Rauniyar, Jiaoyang Li, Sebastian Scherer
Multi-Agent Path Finding (MAPF) is a fundamental problem in robotics and AI, with numerous applications in real-world scenarios. One such scenario is filming scenes with multiple a…
Greedy Perspectives: Multi-Drone View Planning for Collaborative Perception in Cluttered Environments
Krishna Suresh, Aditya Rauniyar, Micah Corah +1
Deployment of teams of aerial robots could enable large-scale filming of dynamic groups of people (actors) in complex environments for applications in areas such as team sports and…