Robohub.org
 

Futuristic vehicle interface with a predictive direct and gesture based input system from Alps Electric


by
17 October 2012



share this:
12-0185-r

Alps Electric has developed a next-generation vehicle interface, created using its own sensors and input devices. The interface consists of a Multi-Modal Commander, allowing for direct and gesture based input, as well as a Haptic Shifter which changes settings according to the situation.

The Multimodal Commander is a hemispherical device with a capacitive sensor and a near-infrared sensor. It can be operated intuitively not only by touch, but also by moving your hand around it. It also supports gesture input, using the space at the top of the device.

“The system has to detect whether the user is really reaching out to use it, or is just moving their hand nearby. This detection is done by creating a kind of curtain with infrared. If a hand goes inside the curtain, and gets close to the Commander, the system deduces that the hand is approaching to use it.”

On the other hand, the Haptic Shifter, a next-generation shift lever, enables the shift gate and load settings to be changed, in line with the user’s preferences.

“Haptic technology means we can create a variety of sensations. This device can change the shift gate from I to H shaped. It can also guide the user automatically when changing from low gear to second.”

In addition, those operations can be predicted, through the behavior-predicting IR sensor. This enables the device guidance capability to be called up before a device is touched. This is achieved using optical flow to detect hand motion vectors. The system can also guess who the user is, so it can provide different menus for the driver’s and passenger’s seats.

“We’d like to release this in 5 to 6 years. We’d like to market it not only for operating all kinds of equipment, but also as a way of making cars adapt to people. That would make cars fun to drive, by combining entertainment with driving.”




DigInfo TV is a Tokyo-based online video news platform dedicated to producing original coverage of cutting edge technology, research and products from Japan.
DigInfo TV is a Tokyo-based online video news platform dedicated to producing original coverage of cutting edge technology, research and products from Japan.





Related posts :



Robot Talk Episode 135 – Robot anatomy and design, with Chapa Sirithunge

  28 Nov 2025
In the latest episode of the Robot Talk podcast, Claire chatted to Chapa Sirithunge from University of Cambridge about what robots can teach us about human anatomy, and vice versa.

Learning robust controllers that work across many partially observable environments

  27 Nov 2025
Exploring designing controllers that perform reliably even when the environment may not be precisely known.

Human-robot interaction design retreat

  25 Nov 2025
Find out more about an event exploring design for human-robot interaction.

Robot Talk Episode 134 – Robotics as a hobby, with Kevin McAleer

  21 Nov 2025
In the latest episode of the Robot Talk podcast, Claire chatted to Kevin McAleer from kevsrobots about how to get started building robots at home.

ACM SIGAI Autonomous Agents Award 2026 open for nominations

  19 Nov 2025
Nominations are solicited for the 2026 ACM SIGAI Autonomous Agents Research Award.

Robot Talk Episode 133 – Creating sociable robot collaborators, with Heather Knight

  14 Nov 2025
In the latest episode of the Robot Talk podcast, Claire chatted to Heather Knight from Oregon State University about applying methods from the performing arts to robotics.

CoRL2025 – RobustDexGrasp: dexterous robot hand grasping of nearly any object

  11 Nov 2025
A new reinforcement learning framework enables dexterous robot hands to grasp diverse objects with human-like robustness and adaptability—using only a single camera.



 

Robohub is supported by:




Would you like to learn how to tell impactful stories about your robot or AI system?


scicomm
training the next generation of science communicators in robotics & AI


 












©2025.05 - Association for the Understanding of Artificial Intelligence