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DROIDS Daily- Robotic News. May 15, 2026
Published 1 day, 10 hours ago
Description
- Lunar rover planner: JAXA’s new hierarchical reinforcement learning system autonomously plans multi-sol traverses, optimizing for terrain, slip, and thermal risk while cutting human replanning time by over 60% in field trials.
- Anti-jamming swarm control: Harvard researchers show that injecting tuned randomness into each robot’s motion policy prevents congestion-induced deadlocks, preserving throughput as swarm size grows in warehouse-like and other multi-robot environments.
- Agriculture to microrobots: A tomato-harvesting robot uses self-supervised, multimodal transformers to assess harvestability, while light-powered salt-grain microrobots integrate sensing, logic, memory, and actuation for untethered micro-scale tasks.
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