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cs.RO2026

GASP: GPU-Accelerated Safe Planner for Real-Time Collision-Aware Motion Generation with Latent Trajectory Sampling

Colin Merk, Stefanos Charalambous, Peter Dürr +1

We present GASP, a GPU-Accelerated Safe Planner for real-time, collision-aware joint-space motion generation in known environments. GASP combines a clamped B-spline trajectory para…

cs.RO2026

Ace! Motion Planning of Professional-Level Table Tennis Serves with a Robot Arm

Guillem Torrente, Guilherme Jorge Maeda, Divij Grover +3

Table tennis, a dynamic, compact, and popular sport, has received significant attention as a robotics benchmark over the last decades. Most of the research has focused on the rally…

cs.RO2026

Physics Models for Sim-to-Real Transfer in Professional-Level Robot Table Tennis

Christian Conti, Bilan Yang, Alexander Sigrist +4

At competitive speeds and spins, a table tennis ball follows complex, counterintuitive trajectories that a robot must track and precisely counter within fractions of a second. Trai…

cs.RO2026

Hardware Design for Table Tennis Robot Capable of Beating Professional Players

Nobuhiko Mukai, Pavel Adodin, Stefan Heusser +6

This paper focuses on the hardware specifications required for a table tennis robot to beat professional players. After analyzing the motions of elite players, we defined target sp…

cs.RO2026

Bridging the sim2real gap in the table tennis robot with a transformer-based ball states predictor

Yin Bi, Christian Conti, Bilan Yang +3

Robotic table tennis is a representative benchmark for high-speed, closed-loop robotic control in dynamic environments, where accurate and fast prediction of ball states is critica…