15 citations · 40 across the 25 of their papers we have counts for
20 papers · 1 filter
YUBI-Real2Sim: 3DGS Scene Verification for Reliable Policy Evaluation
Hiroki Nishizawa, Takehiko Ohkawa, Nicola Scianca +3
Evaluating VLA policies on real robots is costly, time-consuming, and difficult to reproduce, making real-to-sim simulation essential for scalable evaluation. While 3D Gaussian Spl…
YUBI-STAG: Contact and Semantic-Rich Alignment for VLAs via Automated Video-Language Grounding
Masatoshi Tateno, Takehiko Ohkawa, Yueh-Hua Wu +4
Vision-Language-Action (VLA) models acquire broad manipulation capabilities via large-scale pretraining, yet eliciting them through language requires fine-grained alignment between…
RoboPace: Contact-Aware Time-Optimal Retiming for Action-Chunk Policies
Mimo Shirasaka, Takehiko Ohkawa, Takuya Okubo +3
Robot manipulation data collection has been shifting from teleoperation toward robot-free demonstrations, through interfaces such as the Universal Manipulation Interface (UMI) or d…
CounterAlign: Counterfactual Supervision for Vision-Language-Action Models
Haru Kondoh, Kei Ota, Asako Kanezaki +1
Vision-Language-Action (VLA) models are typically trained with behavior cloning (BC) on expert demonstrations. However, BC provides only positive supervision for expert actions, wi…
Auditing Instruction-Trajectory Mismatches in Multimodal Robot Demonstrations
Simon Holk, Ryosuke Takanami, Tatsuya Matsushima +4
Robot demonstration datasets used to train vision-language-action policies can contain a subtle but harmful failure mode: trajectories that are behaviorally correct but paired with…
YUBI: Yielding Universal Bidigital Interface for Bimanual Dexterous Manipulation at Scale
Takehiko Ohkawa, Jumpei Arima, Yuki Noguchi +16
We introduce Yielding Universal Bidigital Interface (YUBI), a finger-aligned gripper designed to enable intuitive, ergonomic, and scalable data collection for bimanual dexterous ma…
See Less, Specify More: Visual Evidence Budgets for Generalizable VLAs
Yueh-Hua Wu, Tatsuya Matsushima, Kei Ota
Generalization remains a central bottleneck for vision-language-action (VLA) models: under distractors, appearance shifts, and semantically similar tasks, the policy must often inf…
Continuous Reasoning for Vision-Language-Action
Yueh-Hua Wu, Tatsuya Matsushima, Kei Ota
Natural language is a powerful reasoning medium for language and vision-language models, but it is mismatched to the granularity of continuous control. Text and explicit subgoals o…
Touch2Insert: Zero-Shot Peg Insertion by Touching Intersections of Peg and Hole
Masaru Yajima, Yuma Shin, Rei Kawakami +2
Reliable insertion of industrial connectors remains a central challenge in robotics, requiring sub-millimeter precision under uncertainty and often without full visual access. Visi…
Simultaneous Extrinsic Contact and In-Hand Pose Estimation via Distributed Tactile Sensing
Mark Van der Merwe, Kei Ota, Dmitry Berenson +2
Prehensile autonomous manipulation, such as peg insertion, tool use, or assembly, require precise in-hand understanding of the object pose and the extrinsic contacts made during in…
Analytic Conditions for Differentiable Collision Detection in Trajectory Optimization
Akshay Jaitly, Devesh K. Jha, Kei Ota +1
Optimization-based methods are widely used for computing fast, diverse solutions for complex tasks such as collision-free movement or planning in the presence of contacts. However,…
Learning Pivoting Manipulation with Force and Vision Feedback Using Optimization-based Demonstrations
Yuki Shirai, Kei Ota, Devesh K. Jha +1
Non-prehensile manipulation is challenging due to complex contact interactions between objects, the environment, and robots. Model-based approaches can efficiently generate complex…
Modality Selection and Skill Segmentation via Cross-Modality Attention
Jiawei Jiang, Kei Ota, Devesh K. Jha +1
Incorporating additional sensory modalities such as tactile and audio into foundational robotic models poses significant challenges due to the curse of dimensionality. This work ad…
Zero-Shot Peg Insertion: Identifying Mating Holes and Estimating SE(2) Poses with Vision-Language Models
Masaru Yajima, Kei Ota, Asako Kanezaki +1
Achieving zero-shot peg insertion, where inserting an arbitrary peg into an unseen hole without task-specific training, remains a fundamental challenge in robotics. This task deman…
Autonomous Robotic Assembly: From Part Singulation to Precise Assembly
Kei Ota, Devesh K. Jha, Siddarth Jain +5
Imagine a robot that can assemble a functional product from the individual parts presented in any configuration to the robot. Designing such a robotic system is a complex problem w…
Robust In-Hand Manipulation with Extrinsic Contacts
Boyuan Liang, Kei Ota, Masayoshi Tomizuka +1
We present in-hand manipulation tasks where a robot moves an object in grasp, maintains its external contact mode with the environment, and adjusts its in-hand pose simultaneously.…
Tactile Estimation of Extrinsic Contact Patch for Stable Placement
Kei Ota, Devesh K. Jha, Krishna Murthy Jatavallabhula +2
Precise perception of contact interactions is essential for fine-grained manipulation skills for robots. In this paper, we present the design of feedback skills for robots that mus…
Tactile-Filter: Interactive Tactile Perception for Part Mating
Kei Ota, Devesh K. Jha, Hsiao-Yu Tung +1
Humans rely on touch and tactile sensing for a lot of dexterous manipulation tasks. Our tactile sensing provides us with a lot of information regarding contact formations as well a…
H-SAUR: Hypothesize, Simulate, Act, Update, and Repeat for Understanding Object Articulations from Interactions
Kei Ota, Hsiao-Yu Tung, Kevin A. Smith +5
The world is filled with articulated objects that are difficult to determine how to use from vision alone, e.g., a door might open inwards or outwards. Humans handle these objects…
Deep Reactive Planning in Dynamic Environments
Kei Ota, Devesh K. Jha, Tadashi Onishi +5
The main novelty of the proposed approach is that it allows a robot to learn an end-to-end policy which can adapt to changes in the environment during execution. While goal conditi…