Questions tagged [robotics]

Question 1

How far are we from developing a robot that can cook at a stove with utensils pots and ingredients, and that can be operated with a visor and limb remote controls?

Question 2

I am trying to use PPO algorithm to train a novel robotic manipulator to reach a target position in its workspace. What should I include to the observation vector, which works as the input to the ...

Question 3

I’m working on a system where agents must move scattered objects (aggregates) from various locations (cells) to a target zone. The environment is divided into a grid of cells, where each cell contains ...

Question 4

I am learning classical planning techniques, and I know many examples of robots are in books. However, I am more curious about the real-world usage of these techniques. Are PDDL and classical planners ...

Question 5

Recently, I have seen papers about large datasets for robotics such as DROID(https://droid-dataset.github.io/) or Open X-Embodiment(https://robotics-transformer-x.github.io/). As I see, the datasets ...

Question 6

I am new to the RL community and I am working on projects about using RL to control robots like drones to fly in the scenes. I have been using Nvidia's Issac Gym for some time, but I have a question ...

Question 7

Which type of Machine Learning is used in robots? Is it supervised learning or unsupervised learning or Reinforcement learning? Especially the robots that were sent in space?

Question 8

Moravec's paradox is the observation in artificial intelligence and robotics that, contrary to traditional assumptions, reasoning requires very little computation, but sensorimotor and perception ...

Question 9

I have never tried reinforcement learning in my life. I'm planning to apply it in robotics. I have some experiences using supervised learning mainly deep learning. So, that's mean I will use neural ...

Question 10

The agent is supposed to visit specific locations (which is also different each time) and it may encounters obstacles. The goal is to visit those locations with the shortest path possible without ...

Question 11

Can an agent trained with a DQN algorithm in a grid world, avoid obstacles (randomly appearing during the run time) and still find the optimal path to finish a task? The agent is supposed to visit ...

Question 12

Hierarchical Reinforcement Learning is suited to tackle many complex problems such as robotics manipulation. Sticking to this example, the basic idea is that instead of learning a sequence of robotic ...

Question 13

I've been reading this paper that formulates invariant task-parametrized HSMMs. The task parameters are represented in $F$ coordinate systems defined by $\{A_j,b_j\}_{j=1}^F$, where $A_j$ denotes the ...

Question 14

I've been reading this paper that formulates invariant task-parametrized HSMMs. In section 3.1 (Model Learning), the task parameters are represented in $F$ coordinate systems defined by $\{A_j,b_j\}_{...

Question 15

I have been working on some RL project, where the policy is controlling the robot using its joint angles.Throughout the project I have noticed some phenomenon, which caught my attention. I have ...

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Questions tagged [robotics]

How far are we from developing a robot that can cook and be controlled remotely?

For the observation vector as input to the control policy in RL project, should I include important but fixed information?

Creating a Dynamic Heat Map for Multi-Agent Path Planning

Are PDDL and classical planners (e.g. FF) used in industry or consumer products?

Why some papers focus on constructing large dataset from real robots, instead of simulations?

RL simulation: Does the Gym-like RL training solution fits the real-world environments?

Which type of Machine Learning is used in robots? [closed]

What is the current state of AI regarding features of Moravec's paradox, such as sensorimotor & perception skills?

Reinforcement Learning vs Supervised Learning [duplicate]

Can I train an agent with DQN, avoiding obstacles and still finding the optimal path to finish the task?

Can DQN find optimal path while avoiding random obstacles?

What are the limitations of hierarchical reinforcement learning?

How do multiple coordinate systems help in capturing invariant features?

How do I find the data-point with respect to a given frame?

Difficulty in agent's learning with increasing dimensions of continuous actions

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