8 papers
Energy-Regularized Imitation Learning for Force- and Work-Aware Robotic Manipulation
Toshiki Otani, Hiromu Taketsugu, Norimichi Ukita
This paper studies energy-aware manipulation as a physically grounded learning problem. We define a joint-space mechanical-work proxy from joint torque and angular displacement, an…
PRISM: Predictive Representation of Interaction Style and Motion for Social Robot Navigation
Bo-Han Chen, Hiromu Taketsugu, Norimichi Ukita
Humans often observe others before interacting and adjust their behavior accordingly. Robot navigation in crowds, however, often represents pedestrians mainly by observed geometric…
Multi-Person Pose Estimation Evaluation Using Optimal Transportation and Improved Pose Matching
Takato Moriki, Hiromu Taketsugu, Norimichi Ukita
In Multi-Person Pose Estimation, many metrics place importance on ranking of pose detection confidence scores. Current metrics tend to disregard false-positive poses with low confi…
MMCM: Multimodality-aware Metric using Clustering-based Modes for Probabilistic Human Motion Prediction
Kyotaro Tokoro, Hiromu Taketsugu, Norimichi Ukita
This paper proposes a novel metric for Human Motion Prediction (HMP). Since a single past sequence can lead to multiple possible futures, a probabilistic HMP method predicts such m…
Selective Social-Interaction via Individual Importance for Fast Human Trajectory Prediction
Yota Urano, Hiromu Taketsugu, Norimichi Ukita
This paper presents an architecture for selecting important neighboring people to predict the primary person's trajectory. To achieve effective neighboring people selection, we pro…
Human Motion Prediction via Test-domain-aware Adaptation with Easily-available Human Motions Estimated from Videos
Katsuki Shimbo, Hiromu Taketsugu, Norimichi Ukita
In 3D Human Motion Prediction (HMP), conventional methods train HMP models with expensive motion capture data. However, the data collection cost of such motion capture data limits…
Physical Plausibility-aware Trajectory Prediction via Locomotion Embodiment
Hiromu Taketsugu, Takeru Oba, Takahiro Maeda +2
Humans can predict future human trajectories even from momentary observations by using human pose-related cues. However, previous Human Trajectory Prediction (HTP) methods leverage…
Active Transfer Learning for Efficient Video-Specific Human Pose Estimation
Hiromu Taketsugu, Norimichi Ukita
Human Pose (HP) estimation is actively researched because of its wide range of applications. However, even estimators pre-trained on large datasets may not perform satisfactorily d…