Tag Archives: self
#436174 How Selfish Are You? It Matters for ...
Our personalities impact almost everything we do, from the career path we choose to the way we interact with others to how we spend our free time.
But what about the way we drive—could personality be used to predict whether a driver will cut someone off, speed, or, say, zoom through a yellow light instead of braking?
There must be something to the idea that those of us who are more mild-mannered are likely to drive a little differently than the more assertive among us. At least, that’s what a team from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) is betting on.
“Working with and around humans means figuring out their intentions to better understand their behavior,” said graduate student Wilko Schwarting, lead author on the paper published this week in Proceedings of the National Academy of Sciences. “People’s tendencies to be collaborative or competitive often spills over into how they behave as drivers. In this paper we sought to understand if this was something we could actually quantify.”
The team is building a model that classifies drivers according to how selfish or selfless they are, then uses that classification to help predict how drivers will behave on the road. Ideally, the system will help improve safety for self-driving cars by integrating a degree of ‘humanity’ into how their software perceives its surroundings; right now, human drivers and their cars are just another object, not much different than a tree or a sign.
But unlike trees and signs, humans have behavioral patterns and motivations. For greater success on roads that are still dominated by us mercurial humans, the CSAIL team believes, driverless cars should take our personalities into account.
How Selfish Are You?
About how important is your own well-being to you vs. the well-being of other people? It’s a hard question to answer without specifying who the other people are; your answer would likely differ if we’re talking about your friends, loved ones, strangers, or people you actively dislike.
In social psychology, social value orientation (SVO) refers to people’s preferences for allocating resources between themselves and others. The two broad categories people can fall into are pro-social (people who are more cooperative, and expect cooperation from others) and pro-self (pretty self-explanatory: “Me first!”).
Based on drivers’ behavior in two different road scenarios—merging and making a left turn—the CSAIL team’s model classified drivers as pro-social or egoistic. Slowing down to let someone merge into your lane in front of you would earn you a pro-social classification, while cutting someone off or not slowing down to allow a left turn would make you egoistic.
On the Road
The system then uses these classifications to model and predict drivers’ behavior. The team demonstrated that using their model, errors in predicting the behavior of other cars were reduced by 25 percent.
In a left-turn simulation, for example, their car would wait when an approaching car had an egoistic driver, but go ahead and make the turn when the other driver was prosocial. Similarly, if a self-driving car is trying to merge into the left lane and it’s identified the drivers in that lane as egoistic, it will assume they won’t slow down to let it in, and will wait to merge behind them. If, on the other hand, the self-driving car knows that the human drivers in the left lane are prosocial, it will attempt to merge between them since they’re likely to let it in.
So how does this all translate to better safety?
It’s essentially a starting point for imbuing driverless cars with some of the abilities and instincts that are innate to humans. If you’re driving down the highway and you see a car swerving outside its lane, you’ll probably distance yourself from that car because you know it’s more likely to cause an accident. Our senses take in information we can immediately interpret and act on, and this includes predictions about what might happen based on observations of what just happened. Our observations can clue us in to a driver’s personality (the swerver must be careless) or simply to the circumstances of a given moment (the swerver was texting).
But right now, self-driving cars assume all human drivers behave the same way, and they have no mechanism for incorporating observations about behavioral differences between drivers into their decisions.
“Creating more human-like behavior in autonomous vehicles (AVs) is fundamental for the safety of passengers and surrounding vehicles, since behaving in a predictable manner enables humans to understand and appropriately respond to the AV’s actions,” said Schwarting.
Though it may feel a bit unsettling to think of an algorithm lumping you into a category and driving accordingly around you, maybe it’s less unsettling than thinking of self-driving cars as pre-programmed, oblivious robots unable to adapt to different driving styles.
The team’s next step is to apply their model to pedestrians, bikes, and other agents frequently found in driving environments. They also plan to look into other robotic systems acting among people, like household robots, and integrating social value orientation into their algorithms.
Image Credit: Image by Free-Photos from Pixabay Continue reading
Posted in Human Robots
#436042 Video Friday: Caltech’s Drone With ...
Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. We’ll also be posting a weekly calendar of upcoming robotics events for the next few months; here’s what we have so far (send us your events!):
ISRR 2019 – October 6-10, 2019 – Hanoi, Vietnam
Ro-Man 2019 – October 14-18, 2019 – New Delhi, India
Humanoids 2019 – October 15-17, 2019 – Toronto, Canada
ARSO 2019 – October 31-1, 2019 – Beijing, China
ROSCon 2019 – October 31-1, 2019 – Macau
IROS 2019 – November 4-8, 2019 – Macau
Let us know if you have suggestions for next week, and enjoy today’s videos.
Caltech has been making progress on LEONARDO (LEg ON Aerial Robotic DrOne), their leggy thruster powered humanoid-thing. It can now balance and walk, which is quite impressive to see.
We’ll circle back again when they’ve got it jumping and floating around.
[ Caltech ]
Turn the subtitles on to learn how robots became experts at slicing bubbly, melty, delicious cheese.
These robots learned how to do the traditional Swiss raclette from demonstration. The Robot Learning & Interaction group at the Idiap Research Institute has developed an imitation learning technique allowing the robot to acquire new skills by considering position and force information, with an automatic adaptation to new situations. The range of applications is wide, including industrial robots, service robots, and assistive robots.
[ Idiap ]
Thanks Sylvain!
Some amazing news this week from Skydio, with the announcement of their better in every single way Skydio 2 autonomous drone. Read our full article for details, but here’s a getting started video that gives you an overview of what the drone can do.
The first batch sold out in 36 hours, but you can put down a $100 deposit to reserve the $999 drone for 2020 delivery.
[ Skydio ]
UBTECH is introducing a couple new robot kits for the holidays: ChampBot and FireBot.
$130 each, available on October 20.
[ Ubtech ]
NASA’s InSight lander on Mars is trying to use its robotic arm to get the mission’s heat flow probe, or mole, digging again. InSight team engineer Ashitey Trebbi-Ollennu, based at NASA’s Jet Propulsion Laboratory in Pasadena, California, explains what has been attempted and the game plan for the coming weeks. The next tactic they’ll try will be “pinning” the mole against the hole it’s in.
[ NASA ]
We introduce shape-changing swarm robots. A swarm of self-transformable robots can both individually and collectively change their configuration to display information, actuate objects, act as tangible controllers, visualize data, and provide physical affordances. ShapeBots is a concept prototype of shape-changing swarm robots. Each robot can change its shape by leveraging small linear actuators that are thin (2.5 cm) and highly extendable (up to 20cm) in both horizontal and vertical directions.
[ Ryo Suzuki ]
Robot abuse!
Vision 60 legged robot managing unstructured terrain without vision or force sensors in its legs. Using only high-transparency actuators and 2kHz algorithmic stability control… 4-limbs and 12-motors with only a velocity command.
[ Ghost Robotics ]
We asked real people to bring in real products they needed picked for their application. In MINUTES, we assembled the right tool.
This is a cool idea, but for a real challenge they should try it outside a supermarket. Or a pet store.
[ Soft Robotics ]
Good water quality is important to humans and to nature. In a country with as much water as the Netherlands has, ensuring water quality is a very labour-intensive undertaking. To address this issue, researchers from TU Delft have developed a ‘pelican drone’: a drone capable of taking water samples quickly, in combination with a measuring instrument that immediately analyses the water quality. The drone was tested this week at the new Marker Wadden nature area ‘Living Lab’.
[ MAVLab ]
In an international collaboration led by scientists in Switzerland, three amputees merge with their bionic prosthetic legs as they climb over various obstacles without having to look. The amputees report using and feeling their bionic leg as part of their own body, thanks to sensory feedback from the prosthetic leg that is delivered to nerves in the leg’s stump.
[ EPFL ]
It’s a little hard to see, but this is one way of testing out asteroid imaging spacecraft without actually going into space: a fake asteroid and a 2D microgravity simulator.
[ Caltech ]
Drones can help filmmakers do the kinds of shots that would be otherwise impossible.
[ DJI ]
Two long interviews this week from Lex Fridman’s AI Podcast, and both of them are worth watching: Gary Marcus, and Peter Norvig.
[ AI Podcast ]
This week’s CMU RI Seminar comes from Tucker Hermans at the University of Utah, on “Improving Multi-fingered Robot Manipulation by Unifying Learning and Planning.”
Multi-fingered hands offer autonomous robots increased dexterity, versatility, and stability over simple two-fingered grippers. Naturally, this increased ability comes with increased complexity in planning and executing manipulation actions. As such, I propose combining model-based planning with learned components to improve over purely data-driven or purely-model based approaches to manipulation. This talk examines multi-fingered autonomous manipulation when the robot has only partial knowledge of the object of interest. I will first present results on planning multi-fingered grasps for novel objects using a learned neural network. I will then present our approach to planning in-hand manipulation tasks when dynamic properties of objects are not known. I will conclude with a discussion of our ongoing and future research to further unify these two approaches.
[ CMU RI ] Continue reading
Posted in Human Robots