IROS 2026 Best Paper: humanoid robot learns tennis rallies from 5 hours of human motion data
qinzytech · x · 2026-10-10
LATENT, a Best Paper at IROS 2026, taught a Unitree G1 humanoid to sustain tennis rallies with humans using just 5 hours of imperfect human motion data.
- Five amateur players supplied unedited, unlabeled forehands, backhands and footwork; the method combines these movements and corrects racket wrist motion mid-swing
- Real-world eval: 20 human-robot rally matches; forehand return success hit 90.90% vs 16.67% without ball-physics randomization; backhand 77.78% ("success" = landing in the opponent's court, not precise placement)
- Key takeaway: randomizing ball behavior in training was as crucial as imitating human movement
- Limits: deployment still uses motion capture; training only covers returns. Next frontier: replacing mocap with vision, or playing full matches
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