2 citations · 3 across the 8 of their papers we have counts for
9 papers
ReVNM: Learning-Based Visual Navigation from a Remote Camera
Michikuni Eguchi, Kohei Honda, Masafumi Endo +2
Visual Navigation Models (VNMs) enable robots to navigate from egocentric visual observations without geometric localization and planning, but long-range navigation still requires…
Commonsense-Grounded Path Planning from Abstract Instructions
Masafumi Endo, Kohei Honda, Ryo Yonetani
We present \emph{commonsense ranked search} (CoRS), a novel path planner that turns an abstract instruction into a route that follows commonsense. While existing methods respect th…
Orienteering Problem with Uncertain Time-Varying Rewards: Framework and Benchmark for Everyday Service Robotics
Masafumi Endo, Kohei Honda, Yuu Jinnai +1
We present the orienteering problem with uncertain time-varying rewards (OP-UTVR), a novel variant of the orienteering problem (OP). While most existing OP formulations assume rewa…
DRPA-MPPI: Dynamic Repulsive Potential Augmented MPPI for Reactive Navigation in Unstructured Environments
Takahiro Fuke, Masafumi Endo, Kohei Honda +1
Reactive mobile robot navigation in unstructured environments is challenging when robots encounter unexpected obstacles that invalidate previously planned trajectories. Model predi…
Risk-aware Integrated Task and Motion Planning for Versatile Snake Robots under Localization Failures
Ashkan Jasour, Guglielmo Daddi, Masafumi Endo +7
Snake robots enable mobility through extreme terrains and confined environments in terrestrial and space applications. However, robust perception and localization for snake robots…
Towards Local Minima-free Robotic Navigation: Model Predictive Path Integral Control via Repulsive Potential Augmentation
Takahiro Fuke, Masafumi Endo, Kohei Honda +1
Model-based control is a crucial component of robotic navigation. However, it often struggles with entrapment in local minima due to its inherent nature as a finite, myopic optimiz…
Deep Probabilistic Traversability with Test-time Adaptation for Uncertainty-aware Planetary Rover Navigation
Masafumi Endo, Tatsunori Taniai, Genya Ishigami
Traversability assessment of deformable terrain is vital for safe rover navigation on planetary surfaces. Machine learning (ML) is a powerful tool for traversability prediction but…
BenchNav: Simulation Platform for Benchmarking Off-road Navigation Algorithms with Probabilistic Traversability
Masafumi Endo, Kohei Honda, Genya Ishigami
As robotic navigation techniques in perception and planning advance, mobile robots increasingly venture into off-road environments involving complex traversability. However, select…
Risk-aware Path Planning via Probabilistic Fusion of Traversability Prediction for Planetary Rovers on Heterogeneous Terrains
Masafumi Endo, Tatsunori Taniai, Ryo Yonetani +1
Machine learning (ML) plays a crucial role in assessing traversability for autonomous rover operations on deformable terrains but suffers from inevitable prediction errors. Especia…