Robotic Cooperative Manipulation

Key responsibilities:
Formulate and develop algorithms into code, and run experiments using mobile robot platform in the
area of sequence generation for object manipulation

Intern Position Introduction

Currently, HRI-US (Silicon Valley) is offering research internships to highly motivated PhD (and qualified MS) students.  Interns will work closely with HRI researchers, and...

Vehicle Motion Prediction

This position will focus on long-term vehicle motion prediction using probabilistic or learning-based methods. We will use both simulated data as well real data gather from on-board sensors to...

Motion Planning/Decision Making

Key responsibilities:
- Develop RL algorithms to develop decision making and motion planning algorithms
- Develop IRL/LfD/Behavior Cloning algorithms to address driving scenarios

Robotics Tactile Manipulation

Key responsibilities:
Formulate and develop algorithms into codes, and run experiments using manipulator with tactile sensors in the area of tactile manipulation and machine learning

Robotic Manipulation of Deformable Objects

Key responsibilities:
Formulate and develop algorithms into codes, and run experiments using mobile robot platform in the area of deformable object manipulation deep reinforcement learning

Physical Human-Robot Interaction

This internship position focuses on formulating and developing algorithms, and running experiments of physical human-robot interaction (pHRI).

Robotics Navigation in a Crowded Environment

This internship position focuses on formulating and developing algorithms, and running experiments on the topic of Robotic “mobility decision making” (e.g. global planning, local movement...

Human-Based Computation and Crowdsourcing

This position offers the opportunity to study human-computing for crowdsourcing based methods to accelerate data acquisition and quality control for machine learning applied to computer...

Simulation Based Human Factors Study

This position offers the opportunity to design and conduct human-factors study to prototype in-car HMIs on our experimental simulator setups.

Machine Learning on Time Series Data (Video/Car Sensor Signals)

The title includes multiple positions which focus on developing and evaluating novel machine learning frameworks using on-road driving data collected from our highly advanced test-vehicles.

Captioning and Retrieval of Events in Traffic Scenes

In a related project at HRI, researchers are developing computer vision and machine learning algorithms for classification of atomic actions of ego-vehicles, traffic participants, and their...

Traffic Scene Classification from Video

This project focuses on research and development of computer vision and machine learning algorithms for video based classification/recognition of road scenes, including places, road surface and...

3D Computer Vision in Dynamic Traffic Scenes

This project focuses on development of computer vision and machine learning algorithms related to processing and fusion of 2D video and 3D point cloud data, including segmentation, recognition,...

Human Action and Intention Recognition

This project focuses on development of computer vision and machine learning algorithms for pedestrian action and intention prediction for next generation mobility systems with emphasis on traffic...

Statement of Privacy (Last Updated 5/23/2017)

American Honda Motor Co., Inc. (“American Honda”) recognizes that your privacy is important. This Privacy Policy is designed to explain how we collect, use and disclose...

2X AD Vehicle


2X AD Vehicle

Honda Research Institute Driving Dataset

Honda Research Institute Driving Dataset

Scientist: Human Machine Interface

This position offers the opportunity to conduct innovative research on a broad set of problems related to human-machine interface for automated/semi-automated vehicles.

Software Engineer

​As part of our System Integration Group, the candidate will be in charge of designing and developing a scalable and reliable software architecture for our Autonomous Driving activities. He/she...


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.