Machine Learning for Robot Navigation

This position seeks a candidate who can participate and contribute to the research of robot navigation in human co-existing environments. In particular, we seek an individual with extensive...

Scientist: Machine Learning for Multimodal Time Series Data

This position offers the opportunity to conduct innovative research on a broad set of problems related to scene and driver understanding. The successful candidate focuses on research and...

Intern Position Introduction

Thank you for your interest, but we have no openings at this time.  Please check back for updates.

About Us

About Us ​Honda Research Institute, USA was established in 2003 as North America's advanced research center that provides innovative...

Honda Nano-technology has promise for new class of electronics

Microscopic carbon nanotubes a hundred thousand times thinner than a human hair may have the potential to transport electricity faster and over greater distances with minimal loss of energy.

Physical Human Driver Interaction

We compute various musculoskeletal indicators of human performance when the driver is operating a vehicle under normal and emergency maneuvering.

Suspended Graphene

Suspended Graphene

Honda Testing Innovative Automated Vehicle Technology at Bay Area Navy Base

Honda has commenced testing of its automated and connected vehicle technology at the Concord Naval Weapons Station (CNWS) in the San Francisco Bay Area.

HRI Silicon Valley has a new office

The Mountain View office is relocating to 375 Ravendale Dr. in Mountain View.

Ultrasensitive sensors made from boron-doped Graphene

Ultrasensitive gas sensors based on the infusion of boron atoms into graphene—a tightly bound matrix of carbon atoms—may soon be possible, according to an international team of...

Honda's efforts in Augmented Reality covered alongside other key players

Honda's efforts in augmented reality are put in context with other industry players.

Live demonstrations of the Honda humanoid robot at IROS 2011

Live demonstrations of the Honda humanoid robot at IROS 2011

3D Head Pose Estimation with Optical Flow and Depth Constraints

3D Head Pose Estimation with Optical Flow and Depth Constraints

Work in progress: A constructivist didactic methodology for a humanoid robotics workshop

Work in progress: A constructivist didactic methodology for a humanoid robotics workshop

Whole-Body Control from Upper Body Task Specifications.

Whole-Body Control from Upper Body Task Specifications.

Whole body humanoid control from human motion descriptors

Whole body humanoid control from human motion descriptors

Visualization of Large Experimental Space Using Holographic Mapping and Artificial Neural Networks. Benchmark Analysis of Multicomponent Catalysts for the Water Gas Shift Reaction

Visualization of Large Experimental Space Using Holographic Mapping and Artificial Neural Networks. Benchmark Analysis of Multicomponent Catalysts for the Water Gas Shift Reaction

Projects

We compute various musculoskeletal indicators of human performance when the driver is operating a vehicle under normal and emergency maneuvering.
The goal of the project is to achieve robust lane-level localization for cars using low cost mass producible sensors.
We have developed online algorithms to transfer motion from a human demonstrator to Honda's humanoid robot, ASIMO.
The development of the next generation green and safe batteries with high energy density is highly desirable for meeting the rapidly growing needs of electrical vehicles.
Rare earth Manganese Oxide (ReMO) as a cathode material has potential capacity higher than that of commercial lithium manganese oxide.
Metal-air batteries are solid state batteries using metal oxidation at the anode and oxygen reduction at the cathode to induce a current flow.
This project is focused on CNT and graphene enforced electrode materials for secondary battery and supercapacitor applications.
This research is focused on scale-up technology for continuous synthesis of SWNTs by CVD method and the exploration of their performance in actual electrochemical devices
The core of this project is for atomistic level understanding of environmental impact on conductivities of SWNTs and 2-D materials in order to reveal their ultimate sensitivities.
Synthesis and studies of growth mechanism, self assembly and properties of low dimensional nanomaterials for alternative energy technologies are at the core of our research.
The goal is to develop driving aids that enhance the driver's situational awareness and give drivers a sense of confidence and trust in the vehicles they are operating.
In Knowledge Discovery, we Integrate knowledge from multiple sources such as Wikipedia, Yahoo Question/Answers, Open Directory Project and OpenMind.
Probabilistic model to track dialog state and provide information to driver viaspoken dialog
This project presents a control theoretic approach for human pose estimation from a set of key feature points detected using depth image streams obtained from a time of flight imaging device.
We are developing a real-time system that detects and tracks traffic participants.
We aim to develop a robust pedestrian detection algorithm that can handle partial occlussions.
We are taking advantage of our autonomous driving platform to create a comprehensive repository of annotated sensor data that provide computer vision benchmarks and training data to support advanced driving assist and autonomous driving applications.
Backing-up of articulated vehicles poses a difficult challenge even for experienced drivers. While long wheelbase dual-axle trailers provide a benefit of increased capacity over their single-axle counterparts, backing-up of such systems is especially difficult. We devise a control strategy for such systems, allowing backing-up maneuvers to be intuitive to drivers without experience with trailers. Using hitch angle feedback, we show these concepts can be used to stabilize the trailer in back-up motion in the presence of arbitrary driver inputs.
Utilizing the latest wearable sensing technologies and patented motion prediction algorithms, the goal is to predict human movement and perform biomechanical computations based on those predictions.