robotics
The Excavator Lifted 6.52 Kilograms Per Cycle
A scaled hydraulic machine combined LiDAR target selection with learned approach, digging and lifting policies.
Summary
A scaled hydraulic machine combined LiDAR target selection with learned approach, digging and lifting policies.
A learning-based excavation stack selected targets from LiDAR elevation maps, used reinforcement learning for approach and loaded transport, and used imitation learning for vision-based digging and lifting. On a scaled hydraulic excavator, the learned digging policy averaged 6.52 kilograms per completed cycle versus 2.68 kilograms for a fixed-dig baseline. Three five-scoop runs demonstrated consecutive operation as the pile changed, but the evidence remains a scaled experimental system rather than full-size field deployment.
Why it matters
A scaled hydraulic machine combined LiDAR target selection with learned approach, digging and lifting policies.
Limits and context
No additional limitation was separately recorded.
Key claims
A scaled hydraulic machine combined LiDAR target selection with learned approach, digging and lifting policies.
Evidence: source-2026-09-25-010
Sources
- arXiv preprint 2609.29750arXiv · primary research
Corrections
No corrections have been recorded for this story.