Robohub.org
 

Why use robots, round 4


by
17 September 2007



share this:

Machines can work continuously, 24/7. Doing so would require power enough to last through the night and either artificial lighting or night vision, and some operations are probably best left for daylight, but they needn’t stop working when the sun goes down. This means that a single machine can manage a greater area than if it were only operating during the day. It’s also useful in limiting damage by deer, which usually come around at night.

 

Machines can make use of senses we don’t possess or which are more sensitive than those we do. Their vision can extend into the infrared and ultraviolet, as well as more finely dividing the visible spectrum, and can also be more detailed and quicker (tracking faster motion) or more accurately track changes over a period of days or weeks. Their hearing can be far sharper than our own. They can be equipped with chemical sensitivity capable of distinguishing between substances we would group together under broad categories, like sweet or acrid. They can also be equipped with radar and sonar, laser ranging and scanning, accurate measures of temperature, humidity, and insolation, and their manipulators can be made to gauge and control pressure more accurately than do our own fingertips. In short, machines can have far better data available to them than would an unassisted human gardener in the same position.

 

Machines can also correlate information very quickly, drawing on recorded data and expert systems to make decisions, and applying heuristics to experience to refine those expert systems. A machine might reasonably be expected to identify to species every plant within the area it was tending, to know whether they were considered crops, benign, weeds, or threatened or endangered, and treat them accordingly. It might be expected to predict to an accuracy of a few days when it could harvest a particular crop, and estimate to within a few percentage points the quantity that could be expected, barring a calamity such as hail or a tornado. It might also be expected to adapt a cropping plan to market conditions, for example putting in more of some crop that hadn’t done well elsewhere and would therefore be in demand.

 

Machines can whisper to each other, via radio links, over distances far greater than a human shout will carry. They can coordinate their activities precisely, cooperating toward a common goal without so much as a hiccup.

 

Machines can, as has recently been demonstrated by DARPA’s autonomous vehicle competitions, operate in an uncontrolled environment.

 

The foregoing is intended as a glimpse of how it might work once development was far along. It presumes a mature technology, some of the pieces of which aren’t yet available or only just beginning to be so.

 

Reposted from Cultibotics.



tags: , , ,


John Payne





Related posts :



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.

Robot Talk Episode 132 – Collaborating with industrial robots, with Anthony Jules

  07 Nov 2025
In the latest episode of the Robot Talk podcast, Claire chatted to Anthony Jules from Robust.AI about their autonomous warehouse robots that work alongside humans.

Teaching robots to map large environments

  05 Nov 2025
A new approach could help a search-and-rescue robot navigate an unpredictable environment by rapidly generating an accurate map of its surroundings.

Robot Talk Episode 131 – Empowering game-changing robotics research, with Edith-Clare Hall

  31 Oct 2025
In the latest episode of the Robot Talk podcast, Claire chatted to Edith-Clare Hall from the Advanced Research and Invention Agency about accelerating scientific and technological breakthroughs.

A flexible lens controlled by light-activated artificial muscles promises to let soft machines see

  30 Oct 2025
Researchers have designed an adaptive lens made of soft, light-responsive, tissue-like materials.

Social media round-up from #IROS2025

  27 Oct 2025
Take a look at what participants got up to at the IEEE/RSJ International Conference on Intelligent Robots and Systems.



 

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