6 papers
Remember to be Curious: Episodic Context and Persistent Worlds for 3D Exploration
Lily Goli, Justin Kerr, Daniele Reda +3
Exploration is a prerequisite for learning useful behaviors in sparse-reward, long-horizon tasks, particularly within 3D environments. Curiosity-driven reinforcement learning addre…
Botany-Bot: Digital Twin Monitoring of Occluded and Underleaf Plant Structures with Gaussian Splats
Simeon Adebola, Chung Min Kim, Justin Kerr +5
Commercial plant phenotyping systems using fixed cameras cannot perceive many plant details due to leaf occlusion. In this paper, we present Botany-Bot, a system for building detai…
Eye, Robot: Learning to Look to Act with a BC-RL Perception-Action Loop
Justin Kerr, Kush Hari, Ethan Weber +5
Humans do not passively observe the visual world -- we actively look in order to act. Motivated by this principle, we introduce EyeRobot, a robotic system with gaze behavior that e…
Omni-Scan: Creating Visually-Accurate Digital Twin Object Models Using a Bimanual Robot with Handover and Gaussian Splat Merging
Tianshuang Qiu, Zehan Ma, Karim El-Refai +4
3D Gaussian Splats (3DGSs) are 3D object models derived from multi-view images. Such "digital twins" are useful for simulations, virtual reality, marketing, robot policy fine-tunin…
Viser: Imperative, Web-based 3D Visualization in Python
Brent Yi, Chung Min Kim, Justin Kerr +8
We present Viser, a 3D visualization library for computer vision and robotics. Viser aims to bring easy and extensible 3D visualization to Python: we provide a comprehensive set of…
Predict-Optimize-Distill: A Self-Improving Cycle for 4D Object Understanding
Mingxuan Wu, Huang Huang, Justin Kerr +4
Humans can resort to long-form inspection to build intuition on predicting the 3D configurations of unseen objects. The more we observe the object motion, the better we get at pred…