22 citations · 34 across the 14 of their papers we have counts for
5 papers · 1 filter
Counterfactual Fairness Filter for Fair-Delay Multi-Robot Navigation
Hikaru Asano, Ryo Yonetani, Mai Nishimura +1
Multi-robot navigation is the task of finding trajectories for a team of robotic agents to reach their destinations as quickly as possible without collisions. In this work, we intr…
When to Replan? An Adaptive Replanning Strategy for Autonomous Navigation using Deep Reinforcement Learning
Kohei Honda, Ryo Yonetani, Mai Nishimura +1
The hierarchy of global and local planners is one of the most commonly utilized system designs in autonomous robot navigation. While the global planner generates a reference path f…
TransPoser: Transformer as an Optimizer for Joint Object Shape and Pose Estimation
Yuta Yoshitake, Mai Nishimura, Shohei Nobuhara +1
We propose a novel method for joint estimation of shape and pose of rigid objects from their sequentially observed RGB-D images. In sharp contrast to past approaches that rely on c…
InCrowdFormer: On-Ground Pedestrian World Model From Egocentric Views
Mai Nishimura, Shohei Nobuhara, Ko Nishino
We introduce an on-ground Pedestrian World Model, a computational model that can predict how pedestrians move around an observer in the crowd on the ground plane, but from just the…
Periodic Multi-Agent Path Planning
Kazumi Kasaura, Ryo Yonetani, Mai Nishimura
Multi-agent path planning (MAPP) is the problem of planning collision-free trajectories from start to goal locations for a team of agents. This work explores a relatively unexplore…