dear all

Sorry for this question but I could not find the meaning of

local j3_space=simOMPL.createStateSpace('j3_space',simOMPL.StateSpaceType.joint_position,jh[3],{-170*math.pi/180},{170*math.pi/180},3)

particularly the the last index 3. In OMPL plugin the function simOMPL.createStateSpace(), it states that 3 stands foruse ForProjection (int): if true, this object position or joint value will be used for computing a default projection.

,

## simOMPL.createStateSpace()

### Re: simOMPL.createStateSpace()

The synopsis for the simOMPL.createStateSpace function is:

Where parameters mean:

I don't know where you find this usage where a value of 3 is passed to it, but it doesn't make sense.

Code: Select all

```
int stateSpaceHandle=simOMPL.createStateSpace(
string name,
int type,
int objectHandle,
table boundsLow,
table boundsHigh,
int useForProjection,
float weight=1.0,
int refObjectHandle=-1
)
```

The parameter you are referring to (useForProjection) is a boolean.name(string): a name for this state space

type(int): type of this state space component (see simOMPL.StateSpaceType)

objectHandle(int): the object handle (a joint object if type is simOMPL.StateSpaceType.joint_position, otherwise a shape)

boundsLow(table of float): lower bounds (if type is pose, specify only the 3 position components)

boundsHigh(table of float): upper bounds (if type is pose, specify only the 3 position components)

useForProjection(int): if true, this object position or joint value will be used for computing a default projection

weight(float, default: 1.0): (optional) the weight of this state space component, used for computing distance between states. Default value is 1.0

refObjectHandle(int, default: -1): (optional) an object handle relative to which reference frame position/orientations will be evaluated. Default value is -1, for the absolute reference frame

I don't know where you find this usage where a value of 3 is passed to it, but it doesn't make sense.

### Re: simOMPL.createStateSpace()

Hi fferi

Thanks a lot for your reply. I have taken it from demo on motionPlanninDemo1.ttt

findPath=function(startConfig,goalConfigs,cnt)

-- Here we do path planning between the specified start and goal configurations. We run the search cnt times,

-- and return the shortest path, and its length

local task=simOMPL.createTask('task')

simOMPL.setAlgorithm(task,simOMPL.Algorithm.RRTConnect)

local j1_space=simOMPL.createStateSpace('j1_space',simOMPL.StateSpaceType.joint_position,jh[1],{-170*math.pi/180},{170*math.pi/180},1)

local j2_space=simOMPL.createStateSpace('j2_space',simOMPL.StateSpaceType.joint_position,jh[2],{-120*math.pi/180},{120*math.pi/180},2)

local j3_space=simOMPL.createStateSpace('j3_space',simOMPL.StateSpaceType.joint_position,jh[3],{-170*math.pi/180},{170*math.pi/180},3)

local j4_space=simOMPL.createStateSpace('j4_space',simOMPL.StateSpaceType.joint_position,jh[4],{-120*math.pi/180},{120*math.pi/180},0)

local j5_space=simOMPL.createStateSpace('j5_space',simOMPL.StateSpaceType.joint_position,jh[5],{-170*math.pi/180},{170*math.pi/180},0)

local j6_space=simOMPL.createStateSpace('j6_space',simOMPL.StateSpaceType.joint_position,jh[6],{-120*math.pi/180},{120*math.pi/180},0)

local j7_space=simOMPL.createStateSpace('j7_space',simOMPL.StateSpaceType.joint_position,jh[7],{-170*math.pi/180},{170*math.pi/180},0)

simOMPL.setStateSpace(task,{j1_space,j2_space,j3_space,j4_space,j5_space,j6_space,j7_space})

simOMPL.setCollisionPairs(task,collisionPairs)

simOMPL.setStartState(task,startConfig)

simOMPL.setGoalState(task,goalConfigs[1])

Thanks a lot for your reply. I have taken it from demo on motionPlanninDemo1.ttt

findPath=function(startConfig,goalConfigs,cnt)

-- Here we do path planning between the specified start and goal configurations. We run the search cnt times,

-- and return the shortest path, and its length

local task=simOMPL.createTask('task')

simOMPL.setAlgorithm(task,simOMPL.Algorithm.RRTConnect)

local j1_space=simOMPL.createStateSpace('j1_space',simOMPL.StateSpaceType.joint_position,jh[1],{-170*math.pi/180},{170*math.pi/180},1)

local j2_space=simOMPL.createStateSpace('j2_space',simOMPL.StateSpaceType.joint_position,jh[2],{-120*math.pi/180},{120*math.pi/180},2)

local j3_space=simOMPL.createStateSpace('j3_space',simOMPL.StateSpaceType.joint_position,jh[3],{-170*math.pi/180},{170*math.pi/180},3)

local j4_space=simOMPL.createStateSpace('j4_space',simOMPL.StateSpaceType.joint_position,jh[4],{-120*math.pi/180},{120*math.pi/180},0)

local j5_space=simOMPL.createStateSpace('j5_space',simOMPL.StateSpaceType.joint_position,jh[5],{-170*math.pi/180},{170*math.pi/180},0)

local j6_space=simOMPL.createStateSpace('j6_space',simOMPL.StateSpaceType.joint_position,jh[6],{-120*math.pi/180},{120*math.pi/180},0)

local j7_space=simOMPL.createStateSpace('j7_space',simOMPL.StateSpaceType.joint_position,jh[7],{-170*math.pi/180},{170*math.pi/180},0)

simOMPL.setStateSpace(task,{j1_space,j2_space,j3_space,j4_space,j5_space,j6_space,j7_space})

simOMPL.setCollisionPairs(task,collisionPairs)

simOMPL.setStartState(task,startConfig)

simOMPL.setGoalState(task,goalConfigs[1])

### Re: simOMPL.createStateSpace()

Hi, was wondering if you could find an answer for your question? I have the same question. Thanks

### Re: simOMPL.createStateSpace()

btw, when I looked at the source code, it seems that if the variable is greater than zero, it is considered True! so in this case, j1, j2 and j3 are considered for projection. However, my second question is about the projection it self! How does it work and what does it mean?

### Re: simOMPL.createStateSpace()

You can read more about state space projections here.

### Re: simOMPL.createStateSpace()

Thanks for your message, I have read that url from OMPL along with many others but what they have provided is simply a 2D projection. In my case, I am using OMPL for my 6dof serial robot (kind of similar to Vrep example) but even in Vrep, the projection is not clear so I am not sure how they are using the projection function to generate the path using SBL. As I understood in Vrep, they are only using j1,j2 and j3 for the projection and not the wrist of the robot.

### Re: simOMPL.createStateSpace()

That is exactly the point: the projection is a lower dimensional space (usually 2d or 3d) because higher dimensions would be unfeasible.

How the projection is used it depends on the planning algorithm. It may be used to estimate coverage and/or to guide exploration of state space, or something else.

With the OMPL plugin you can currently indicate wether a state space component takes place in computing the euclidean projection or not. You have to chose which state space components fit best for your problem.

How the projection is used it depends on the planning algorithm. It may be used to estimate coverage and/or to guide exploration of state space, or something else.

With the OMPL plugin you can currently indicate wether a state space component takes place in computing the euclidean projection or not. You have to chose which state space components fit best for your problem.