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Kensuke Harada

50 accepted papers

2026

A Multi-Level Similarity Approach for Single-View Object Grasping: Matching, Planning, and Fine-Tuning

ICRA 2026poster

Grasping unknown objects from a single view has remained a challenging topic in robotics due to the uncertainty of partial observation. Recent advances in large-scale models have led to benchmark solutions such as GraspNet-1Billion. However, such learning-based approaches still face a critical limit…

2026

Bimanual Regrasp Planning and Control for Active Reduction of Object Pose Uncertainty

ICRA 2026poster

Precisely grasping an object is a challenging task due to pose uncertainties. Conventional methods have used cameras and fixtures to reduce object uncertainty. They are effective but require intensive preparation, such as designing jigs based on the object geometry and calibrating cameras with high-…

2026

Clearance-Adaptive Grasping of Clustered Objects Using Pin-Array Robotic Fingers Under Uncertainty

RA-L 2026

Clustered-object environments challenge robotic grasp planning and implementation mainly for two reasons: (i) the limited inter-object clearance leaves insufficient space for conventional gripper fingers to approach and wrap the target object without collisions, and (ii) perception-induced position

Cited by 0SourceScholar
2026

Learning From Planned Data to Improve Robotic Pick-and-Place Planning Efficiency

RA-L 2026

This work proposes a learning method to accelerate robotic pick-and-place planning by predicting shared grasps. Shared grasps are defined as grasp poses feasible to both the initial and goal object configurations in a pick-and-place task. Traditional analytical methods for solving shared grasps eval

Cited by 2SourceScholar
2026

Learning from Planned Data to Improve Robotic Pick-And-Place Planning Efficiency

ICRA 2026poster

This work proposes a learning method to accelerate robotic pick-and-place planning by predicting shared grasps. Shared grasps are defined as grasp poses feasible to both the initial and goal object configurations in a pick-and-place task. Traditional analytical methods for solving shared grasps eval…

2026

Prompt2Craft: Generating Functional Craft Assemblies With LLMs

RA-L 2026

The Craft Assembly Task - a robotic assembly task inspired by handmade crafts - poses unique challenges relative to a traditional object assembly task.It involves open-ended decisions that are difficult to automate, with previous work relying on prior assumptions or expert knowledge, limiting scalab

Cited by 0SourceScholar
2026

Stiffness Map Generation for Soft Materials Using Axis-Aligning Non-Contact Measuring Device

RA-L 2026

This paper presents a novel non-contact sensing device for constructing stiffness distribution maps on soft-material surfaces. Since directly contacting and measuring each point is inefficient, the device applies an air jet to the surface to induce deformation, and the resulting displacement is meas

Cited by 0SourceScholar
2026

Zero-Shot Recognition of Test Tube Types by Automatically Collecting and Labeling RGB Data

ICRA 2026poster

This work presents a method for automatically detecting and recognizing test tube types in a rack. It leverages automatic segmentation, clustering, and labeling processes to eliminate the need for explicitly preparing training data. These processes are addressed by using combined global prediction a…

Cited by 0SourceScholar
2025

Adaptive Grasping of Moving Objects in Dense Clutter via Global-to-Local Detection and Static-to-Dynamic Planning

ICRA 2025

Robotic grasping is facing a variety of real-world uncertainties caused by non-static object states, unknown object properties, and cluttered object arrangements. The difficulty of grasping increases with the presence of more uncertainties, where commonly used learning-based approaches struggle to p

Cited by 0SourceScholar
2025

Assembly Sequence Planning Considering Robotic Motion Costs and Multi-Operation Constraints

IROS 2025

In assembly tasks, multiple operations, such as positioning, snap-fitting, and screw fastening, are often required for a single workpiece. The multiple operations add complexity to the planning process. To address this challenge, we propose an assembly sequence planning method that considers the com

Cited by 0SourceScholar
2025

Bimanual Regrasp Planning and Control for Active Reduction of Object Pose Uncertainty

RA-L 2025

Precisely grasping an object is a challenging task due to pose uncertainties. Conventional methods have used cameras and fixtures to reduce object uncertainty. They are effective but require intensive preparation, such as designing jigs based on the object geometry and calibrating cameras with high-

Cited by 2SourceScholar
2025

Preference Aligned Diffusion Planner for Quadrupedal Locomotion Control

IROS 2025

Diffusion models demonstrate superior performance in capturing complex distributions from large-scale datasets, providing a promising solution for quadrupedal locomotion control. However, the robustness of the diffusion planner is inherently dependent on the diversity of the pre-collected datasets.

Cited by 9SourcecodeScholar
2025

Zero-Shot Recognition of Test Tube Types by Automatically Collecting and Labeling RGB Data

RA-L 2025

This work presents a method for automatically detecting and recognizing test tube types in a rack. It leverages automatic segmentation, clustering, and labeling processes to eliminate the need for explicitly preparing training data. These processes are addressed by using combined global prediction a

Cited by 0SourceScholar
2024

Component Selection for Craft Assembly Tasks

RA-L 2024

Inspired by traditional handmade crafts, where a person improvises assemblies based on the available objects, we formally introduce the Craft Assembly Task. It is a robotic assembly task that involves building an accurate representation of a given target object using the available objects, which do

Cited by 1SourceScholar
2024

NBV/NBC Planning Considering Confidence Obtained From Shape Completion Learning

RA-L 2024

In this letter, we present a novel approach for planning an object's Next Best Views (NBV) so that a depth camera can collect the object's surface point cloud and reconstruct its 3D model with a small number of consequent views. Our focus is especially on thin and curved metal plates, and we use a r

Cited by 3SourceScholar
2023

A Stiffness-Changeable Soft Finger Based on Chain Mail Jamming

ICRA 2023poster

This paper presents a stiffness-changeable soft finger using chain mail jamming. This finger can achieve adaptive grasping and in-hand manipulation by reshaping and exerting changeable gripping force. The jamming phenomenon happens when particles in a chamber get interlocked where confining pressure…

Cited by 7SourceScholar
2023

Learning Efficient Policies for Picking Entangled Wire Harnesses: An Approach to Industrial Bin Picking

RA-L 2023

Wire harnesses are essential connecting components in manufacturing industry but are challenging to be automated in industrial tasks such as bin picking. They are long, flexible and tend to get entangled when randomly placed in a bin. This makes it difficult for the robot to grasp a single one in de

Cited by 27SourcecodeScholar
2023

Learning to Dexterously Pick or Separate Tangled-Prone Objects for Industrial Bin Picking

RA-L 2023

Industrial bin picking for tangled-prone objects requires the robot to either pick up untangled objects or perform separation manipulation when the bin contains no isolated objects. The robot must be able to flexibly perform appropriate actions based on the current observation. It is challenging due

Cited by 5SourceScholar
2023

Probabilistic Slide-support Manipulation Planning in Clutter

IROS 2023poster

To safely and efficiently extract an object from the clutter, this paper presents a bimanual manipulation planner in which one hand of the robot is used to slide the target object out of the clutter while the other hand is used to support the surrounding objects to prevent the clutter from collapsin…

Cited by 1SourceScholar
2022

Category-Association Based Similarity Matching for Novel Object Pick-and-Place Task

RA-L 2022

Robotic pick-and-place has been researched for a long time to cope with uncertainty of novel objects and changeable environments. Past works mainly focus on learning-based methods to achieve high precision. However, they have difficulty being generalized for the limitation of specified training mode

Cited by 13SourceScholar
2022

Efficient Task/Motion Planning for a Dual-arm Robot from Language Instructions and Cooking Images

IROS 2022poster

When generating robot motions based on instructions such as cooking recipes, ambiguity of the instructions and lack of necessary information are problematic for the robot. To solve this problem, we propose an efficient motion planning approach for a dual-arm robot by constructing a graph repre-senti…

Cited by 23SourceScholar
2022

Metal Wire Manipulation Planning for 3D Curving - A Low Payload Robot that Uses a Bending Machine to Bend High-Stiffness Wire

IROS 2022poster

This paper presents a combined task and motion planner for a robot arm to carry out 3D metal wire curving tasks by collaborating with a bending machine. We assume a collaborative robot that is safe to work in a human environment but has a weak payload to bend objects with large stiffness, and develo…

Cited by 3SourceScholar
2021

Assembly Action Understanding from Fine-Grained Hand Motions, a Multi-camera and Deep Learning Approach

IROS 2021poster

This article presents a novel software architecture enabling the analysis of assembly actions from fine-grained hand motions. Unlike previous works that compel humans to wear ad-hoc devices or visual markers in the human body, our approach enables users to move without additional burdens. Modules de…

Cited by 13SourceScholar
2021

Assembly Planning by Recognizing a Graphical Instruction Manual

IROS 2021poster

This paper proposes a robot assembly planning method by automatically reading the graphical instruction manuals designed for humans. Essentially, the method generates an Assembly Task Sequence Graph (ATSG) by recognizing a graphical instruction manual. An ATSG is a graph describing the assembly task…

Cited by 13SourceScholar
2021

Efficient Picking by Considering Simultaneous Two-Object Grasping

IROS 2021poster

This paper presents a motion planning algorithm that enables robots to efficiently pick up objects by considering simultaneous multi-object grasping. At the center of the algorithm is a cost function that helps to determine one of the following three grasping policies considering distance and fricti…

Cited by 15SourceScholar
2021

Online Object Searching by a Humanoid Robot in an Unknown Environment

RA-L 2021

This letter proposes a framework for an autonomous humanoid robot, aimed at searching for a target object in an unknown environment using 3D-simultaneous localization and mapping (SLAM). The robot determines, while walking, the next viewpoint from an environment map and aggregated object recognition

Cited by 15SourceScholar
2021

Robotic Imitation of Human Assembly Skills Using Hybrid Trajectory and Force Learning

ICRA 2021poster

Robotic assembly tasks involve complex and low-clearance insertion trajectories with varying contact forces at different stages. While the nominal motion trajectory can be easily obtained from human demonstrations through kinesthetic teaching, teleoperation, simulation, among other methods, the forc…

Cited by 31SourceScholar
2020

Functionally Divided Manipulation Synergy for Controlling Multi-fingered Hands

IROS 2020poster

Synergy provides a practical approach for expressing various postures of a multi-fingered hand. However, a conventional synergy defined for reproducing grasping postures cannot perform in-hand manipulation, e.g., tasks that involve simultaneously grasping and manipulating an object. Locking the posi…

Cited by 9SourceScholar
2020

Learning Force Control for Contact-Rich Manipulation Tasks With Rigid Position-Controlled Robots

RA-L 2020

Reinforcement Learning (RL) methods have been proven successful in solving manipulation tasks autonomously. However, RL is still not widely adopted on real robotic systems because working with real hardware entails additional challenges, especially when using rigid position-controlled manipulators.

Cited by 137SourceScholar
2020

Planning an Efficient and Robust Base Sequence for a Mobile Manipulator Performing Multiple Pick-and-place Tasks

ICRA 2020poster

In this paper, we address efficiently and robustly collecting objects stored in different trays using a mobile manipulator. A resolution complete method, based on precomputed reachability database, is proposed to explore collision-free inverse kinematics (IK) solutions and then a resolution complete…

Cited by 47SourceScholar
2019

Learning Based Robotic Bin-picking for Potentially Tangled Objects

IROS 2019poster

In this research, we tackle the challenge of picking only one object from a randomly stacked pile where the objects can potentially be tangled. No solution has been proposed to solve this challenge due to the complexity of picking one and only one object from the bin of tangled objects. Therefore, w…

Cited by 56SourceScholar
2019

Quickly Inserting Pegs into Uncertain Holes using Multi-view Images and Deep Network Trained on Synthetic Data

IROS 2019poster

This paper explores the use of robots to autonomously assemble parts with variations in colors and textures. Specifically, we focus on peg-in-hole assembly with some initial position uncertainty and holes located on surfaces of different colors and textures. Two in-hand cameras and a force-torque se…

Cited by 79SourceScholar
2017

Online robot introspection via wrench-based action grammars

IROS 2017poster

Robotic failure is all too common in unstructured robot tasks. Despite well-designed controllers, robots often fail due to unexpected events. Robots under a sense-plan-act paradigm do not have an additional loop to check their actions. In this work, we present a principled methodology to bootstrap o…

Cited by 22SourceScholar
2016

An empirical comparison among the effect of different supports in sequential robotic manipulation

IROS 2016poster

Pick-and-place regrasp extends the manipulation capability of a robot by using a sequence of regrasps to accomplish tasks that are not possible using a single grasp due to constraints such as kinematics or collisions between the robot and the environment. Previous work on pick-and-place only leverag…

Cited by 5SourceScholar
2015

Experimental investigation of effect of fingertip stiffness on resistible force in grasping

ICRA 2015poster

In this study, we experimentally investigated the effect of robot fingertip stiffness on the maximum resistible force. The maximum resistible force is defined as the maximum tangential force at which the fingertip can maintain contact when applying and increasing tangential/shearing force. We includ…

Cited by 27SourceScholar
2015

Grasp stability evaluation based on energy tolerance in potential field

IROS 2015poster

We propose an evaluation method of grasp stability which takes into account the elastic deformation of fingertips from the viewpoint of energy. An evaluation value of grasp stability is derived as the minimum energy which causes slippage of a fingertip on its contact surface. To formulate the evalua…

Cited by 5SourceScholar