activity
20222025
most citedWhen to Replan? An Adaptive Replanning Strategy for Autonomous Navigation using Deep Reinforcement Learning

1 citations · 2 across the 7 of their papers we have counts for

collaborators

7 papers

cs.RO2025

Real-Time Model Predictive Control of Vehicles with Convex-Polygon-Aware Collision Avoidance in Tight Spaces

Haruki Kojima, Kohei Honda, Hiroyuki Okuda +1

This paper proposes vehicle motion planning methods with obstacle avoidance in tight spaces by incorporating polygonal approximations of both the vehicle and obstacles into a model…

cs.RO2025

LVLM-MPC Collaboration for Autonomous Driving: A Safety-Aware and Task-Scalable Control Architecture

Kazuki Atsuta, Kohei Honda, Hiroyuki Okuda +1

This paper proposes a novel Large Vision-Language Model (LVLM) and Model Predictive Control (MPC) integration framework that delivers both task scalability and safety for Autonomou…

cs.RO2024

Switching Sampling Space of Model Predictive Path-Integral Controller to Balance Efficiency and Safety in 4WIDS Vehicle Navigation

Mizuho Aoki, Kohei Honda, Hiroyuki Okuda +1

Four-wheel independent drive and steering vehicle (4WIDS Vehicle, Swerve Drive Robot) has the ability to move in any direction by its eight degrees of freedom (DoF) control inputs.…

cs.RO2023

Stein Variational Guided Model Predictive Path Integral Control: Proposal and Experiments with Fast Maneuvering Vehicles

Kohei Honda, Naoki Akai, Kosuke Suzuki +4

This paper presents a novel Stochastic Optimal Control (SOC) method based on Model Predictive Path Integral control (MPPI), named Stein Variational Guided MPPI (SVG-MPPI), designed…

cs.RO2023★ 1 cited

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…

cs.RO2022★ 1 cited

Generalized LOAM: LiDAR Odometry Estimation with Trainable Local Geometric Features

Kohei Honda, Kenji Koide, Masashi Yokozuka +2

This paper presents a LiDAR odometry estimation framework called Generalized LOAM. Our proposed method is generalized in that it can seamlessly fuse various local geometric shapes…

cs.RO2022

MPC Builder for Autonomous Drive: Automatic Generation of MPCs for Motion Planning and Control

Kohei Honda, Hiroyuki Okuda, Tatsuya Suzuki +1

This study presents a new framework for vehicle motion planning and control based on the automatic generation of model predictive controllers (MPCs) named MPC Builder. In this fram…