8
votes
Motion Planning vs. Control
There is a saying in software engineering which states that your company structure is reflected in your software architecture (I cannot recall the exact phrase). This is true for a robot control ...
5
votes
A* search results in path too close to obstacles
Obstacle padding/ robot padding.
Suppose you are working in a 2D environment and that you have an obstacle of the size 2x2. When doing planning (graph search, etc.), you increase the size of the ...
4
votes
Accepted
Understanding and implementing belief space planning
The kalman filter that you've already been using on single robots can be broadened to apply to the swarm of robots. If you previously represented the state of a single robot with 5 variables, and you ...
3
votes
Applications of Reinforcement Learning
It's true that using RL in robotics involves many challenges, including the usually high dimensionality of problem spaces, the cost and limitations of real-world sessions, the impossibility or ...
3
votes
Motion Planning vs. Control
I can speak to space robotics, and military-type robotics, and some commercial robots, but there isn't really a "typical" robot yet.
How does motion planning differ from controls?
A drunk ...
3
votes
Accepted
What does it actually mean by Task Planning?
I think what you are seeing here is a decade advancement in microprocessor and robotic control technologies.
By the time the second and third papers were written, in 2000 & 1998, the definition ...
3
votes
A* search results in path too close to obstacles
Most planning algorithms reduce your robot to a point and plan a path for that point. The arising problem is exaclty what you are facing. As suggested before, obstacle padding is one of the methods, ...
2
votes
Accepted
What is the best way to compute the probabilistic belief of a robot equipped with a vision sensor?
Use bearings-only localization to model camera informativeness, and simulate measurements with zero noise (e.g., no innovation).
For a variety of reasons, this is actually theoretically sound way of ...
2
votes
why is quadrotor motion planning hard?
The main problem with motion planning is the time-dimension. Not only that the UAV can move up, down, forward or backward, but the motion is also defined along the time-axis. A motion plan like "up, ...
2
votes
Accepted
A Vector Field Histogram implementation in Python 2.7
I'm having a hard time following your code, partly because I don't know Python but I think mostly because I'm not sure I understand your variables. That said, I think I do understand your problem.
...
2
votes
Difference between Single-Query and Multiple Query Algorithms?
I think what you said in your question is correct so far.
Single and multi query planning refers to the number of planning tasks you are about to execute. That means, the number of different paths ...
2
votes
How to use depth map in A* path planning?
I would recommend using some sort of discretized local map. For 3D use octomap (https://octomap.github.io/) and 2D a grid map. But honestly, I would try the laziest option, putting each depth reading ...
1
vote
Ros2: OccupancyGrid with RPlidar
You're combining two seperate problems here. The first is creating an occupancy grid, the second is getting data from the RPlidar. Remember, one of the main reasons we use ROS is because it allows us ...
1
vote
Accepted
Best way to generate a configuration space for a 6 DOF robot
A good start here might be the RRT algorithm (https://en.wikipedia.org/wiki/Rapidly-exploring_random_tree) or one of its many, many variations. Let's assume you're doing this in the configuration ...
1
vote
Matlab smooth transition between stored configurations (rigid body tree robot )
I don't know how you're storing or recalling your presets, but you can put a Rate Limiter block between it and your joint and limit how quickly your joint reference changes.
I made a short clip for ...
1
vote
Path planning algorithm better than RRT* and Artificial Potential Field
My understanding is that most people don't use the raw RRT solution directly. First they smooth it. A google search will yield many papers on this. For example: Improved Path-Finding Algorithm for ...
Ben♦
- 5,825
1
vote
Motion Planning vs. Control
I would answer your first question. I would say motion planning can be treated as a higher-level control. You can think about motion planning problems as a subclass of optimal control problems (OCP).
...
1
vote
Path Planning algorithm
shortest path between 2 points
This spec goes into the cost function design.
maintain a minimum distance to obstacles
Given 2D occupancy grid, threshold probability values to get ...
1
vote
Accepted
Task oriented robot language?
In contrast to motion planning, task planning operates on a symbolic higher level. Often, it's connected to natural language descriptions like “open door” and “stand-up”. This makes it a natural ...
1
vote
What are robot task planners?
Task and motion planning describes different levels of abstraction in a domain. Motion planning is about lowlevel actions for example move the car forward for 1 meter, while task planning is about ...
1
vote
Accepted
Are there any open-source congnative planing frameworks for robotics?
KnowRob is a knowledge processing system that combines knowledge representation and reasoning methods with techniques for acquiring knowledge and for grounding the knowledge in a physical system and ...
1
vote
Are there any open-source congnative planing frameworks for robotics?
Have a look at ROS. They have motion planning packages. Sorry I can't provide more detail at this time, but I know ROS packages exist... and they are open source. This is a good question for their ...
1
vote
Accepted
A* algorithm for Arduino robot path planning
You may find this example useful. I recently used A* for highway driving in traffic, driving at 50 mph and passing other cars.
https://github.com/ericlavigne/CarND-Path-Planning
The A* algorithm ...
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