Categories: FAANG

ARMOR: Egocentric Perception for Humanoid Robot Collision Avoidance and Motion Planning

Humanoid robots have significant gaps in their sensing and perception, making it hard to perform motion planning in dense environments. To address this, we introduce ARMOR, a novel egocentric perception system that integrates both hardware and software, specifically incorporating wearable-like depth sensors for humanoid robots. Our distributed perception approach enhances the robot’s spatial awareness, and facilitates more agile motion planning. We also train a transformer-based imitation learning (IL) policy in simulation to perform dynamic collision avoidance, by leveraging around 86 hours…
AI Generated Robotic Content

Recent Posts

3 Nuclear Startups Hit a Big Milestone. Why It Matters—and Why It Doesn’t

The companies’ Fourth of July plans include celebrating new reactor designs coming online. But there’s…

17 hours ago

Context vs. Memory Engineering in Agentic AI Systems

Compression on Arrival Tool outputs should be compressed after a call returns, not after the…

2 days ago

Why I disappeared for 3 Months & What’s Next

I’ve been quiet since November because I’ve been building.Over the past few months, AI has…

2 days ago

Multi-Agent Teams Hold Experts Back

Multi-agent LLM systems are increasingly deployed as autonomous collaborators, where agents interact freely rather than…

2 days ago

Managing Elasticsearch Reindex at Scale: Performance, Reliability, and Observability

Editor’s Note: This is the fourth post in a series exploring how Palantir customizes infrastructure…

2 days ago

GenPage: Towards End-to-End Generative Homepage Construction at Netflix

Authors: Lequn Wang, Jiangwei Pan, and Linas BaltrunasFigure 1. Autoregressive homepage generation. GenPage builds a…

2 days ago