Robot arm motion planning in ROS - Performance & Optimization

Performance: Robot arm motion planning

HIGH IMPACT

This affects the responsiveness and smoothness of robot arm movements, impacting real-time control and user experience.

Planning robot arm motion for a pick-and-place task

ROS

import moveit_commander
import rospy

rospy.init_node('good_motion_planner')
arm = moveit_commander.MoveGroupCommander('manipulator')

# Use cached plans and incremental updates
cached_plan = arm.plan()
for _ in range(10):
    arm.execute(cached_plan, wait=True)
    # Update only if environment changes

Reusing cached plans and updating only when needed reduces CPU load and improves smoothness.

📈 Performance GainReduces planning time to under 10 ms per execution, enabling smooth continuous motion

Planning robot arm motion for a pick-and-place task

ROS

import moveit_commander
import rospy

rospy.init_node('bad_motion_planner')
arm = moveit_commander.MoveGroupCommander('manipulator')

# Plan with default settings repeatedly without caching
for _ in range(10):
    plan = arm.plan()
    arm.execute(plan, wait=True)

Repeatedly planning from scratch without caching or incremental updates causes high CPU usage and delays.

📉 Performance CostBlocks control loop for 100+ ms per plan, causing jerky arm motion and delayed response

Performance Comparison

Pattern	CPU Usage	Planning Delay	Motion Smoothness	Verdict
Repeated full planning	High (80%+ CPU)	100+ ms per plan	Jerky, delayed	[X] Bad
Cached incremental planning	Low (20-30% CPU)	Under 10 ms per plan	Smooth, responsive	[OK] Good

Rendering Pipeline

Motion planning flows through sensing, path computation, and command execution stages. Heavy computation delays command updates, causing motion lag.

→Path Computation

→Command Execution

⚠️ BottleneckPath Computation due to complex collision checking and inverse kinematics

Optimization Tips

1Avoid full re-planning on every motion command; reuse cached plans when possible.

2Simplify collision models to speed up path computation.

3Use incremental planning to maintain smooth and responsive arm movements.

Performance Quiz - 3 Questions

What is the main performance bottleneck in robot arm motion planning?

A Battery power consumption

B Network communication latency

C Path computation including collision checking

D Sensor calibration time

DevTools: rosbag and rqt_plot

How to check: Record robot state and planning times with rosbag; use rqt_plot to visualize planning duration and CPU load over time.

What to look for: Look for spikes in planning time and CPU usage that correlate with jerky arm movements or delayed commands.

Practice

1. What is the main purpose of robot arm motion planning in ROS?

easy

A. To control the robot's camera settings

B. To calculate safe and smooth paths for the robot arm to move

C. To manage network communication between robots

D. To store sensor data from the robot arm

Solution

1. Step 1: Understand the role of motion planning

   Motion planning calculates paths that avoid obstacles and ensure smooth movement.

2. Step 2: Identify the correct purpose among options

   Only To calculate safe and smooth paths for the robot arm to move describes calculating safe and smooth paths for the robot arm.

3. Final Answer:

   To calculate safe and smooth paths for the robot arm to move -> Option B

4. Quick Check:

   Motion planning = safe, smooth paths [OK]

Hint: Motion planning means planning safe arm movements [OK]

Common Mistakes:

• Confusing motion planning with sensor data handling
• Thinking motion planning controls cameras
• Mixing motion planning with network communication

2. Which of the following is the correct way to create a MoveGroupInterface object for a robot arm named "manipulator" in ROS C++?

easy

A. MoveGroupInterface move_group("robot_arm");

B. MoveGroupInterface move_group = new MoveGroupInterface("manipulator");

C. move_group = MoveGroupInterface("manipulator");

D. moveit::planning_interface::MoveGroupInterface move_group("manipulator");

Solution

1. Step 1: Recall correct MoveGroupInterface syntax

   In ROS C++, the MoveGroupInterface is created with the namespace and constructor: moveit::planning_interface::MoveGroupInterface move_group("group_name");

2. Step 2: Check each option for syntax and group name

   moveit::planning_interface::MoveGroupInterface move_group("manipulator"); uses correct syntax and the correct group name "manipulator". MoveGroupInterface move_group = new MoveGroupInterface("manipulator"); uses incorrect new keyword and assignment. move_group = MoveGroupInterface("manipulator"); lacks type declaration. MoveGroupInterface move_group("robot_arm"); uses wrong group name.

3. Final Answer:

   moveit::planning_interface::MoveGroupInterface move_group("manipulator"); -> Option D

4. Quick Check:

   Correct constructor syntax = moveit::planning_interface::MoveGroupInterface move_group("manipulator"); [OK]

Hint: Use full type and constructor with group name in quotes [OK]

Common Mistakes:

• Using 'new' keyword incorrectly in C++
• Omitting type declaration
• Using wrong group name string

3. Given the following ROS C++ code snippet, what will be the output if planning succeeds?

moveit::planning_interface::MoveGroupInterface move_group("manipulator");
auto success = (move_group.plan(plan) == moveit::planning_interface::MoveItErrorCode::SUCCESS);
if (success) {
  std::cout << "Plan found!" << std::endl;
} else {
  std::cout << "Plan failed." << std::endl;
}

medium

A. Plan found!

B. Plan failed.

C. Compilation error

D. No output

Solution

1. Step 1: Understand the plan() return value check

   The plan() function returns a MoveItErrorCode. Comparing it to SUCCESS means success is true if planning worked.

2. Step 2: Analyze the if condition and output

   If success is true, the code prints "Plan found!"; otherwise, "Plan failed.". Since planning succeeds, output is "Plan found!".

3. Final Answer:

   Plan found! -> Option A

4. Quick Check:

   Plan success prints "Plan found!" [OK]

Hint: Success means plan() returns SUCCESS code [OK]

Common Mistakes:

• Confusing success condition logic
• Assuming plan() returns bool directly
• Ignoring MoveItErrorCode enum comparison

4. Identify the error in this ROS C++ code snippet for robot arm motion planning:

moveit::planning_interface::MoveGroupInterface move_group("manipulator");
move_group.setPoseTarget(target_pose);
move_group.plan(plan);
move_group.execute(plan);

medium

A. Missing check if plan was successful before execute

B. Incorrect method name: should be setTargetPose

C. execute() does not accept a plan argument

D. Missing initialization of MoveGroupInterface

Solution

1. Step 1: Review the planning and execution sequence

   The code sets a target, plans, then executes without checking if planning succeeded.

2. Step 2: Identify the missing safety check

   Best practice is to verify plan success before calling execute to avoid errors or unsafe moves.

3. Final Answer:

   Missing check if plan was successful before execute -> Option A

4. Quick Check:

   Always verify plan success before execute [OK]

Hint: Always check plan success before executing [OK]

Common Mistakes:

• Assuming plan always succeeds
• Confusing method names
• Ignoring return values from plan()

5. You want to plan a motion for a robot arm to reach a target pose but avoid a newly added obstacle in the environment. Which ROS framework feature should you use to update the planning scene before planning?

hard

A. Use RViz to manually move the robot arm

B. Directly modify the MoveGroupInterface target pose to avoid obstacle

C. Use PlanningSceneInterface to add the obstacle and update the scene

D. Restart the ROS node to reload the environment

Solution

1. Step 1: Understand how obstacles affect planning

   Obstacles must be added to the planning scene so the planner knows to avoid them.

2. Step 2: Identify the correct tool to update the planning scene

   PlanningSceneInterface allows adding/removing objects in the environment for planning awareness.

3. Step 3: Evaluate other options

   Modifying target pose doesn't update obstacles. Restarting node is inefficient. RViz manual moves don't affect planning scene programmatically.

4. Final Answer:

   Use PlanningSceneInterface to add the obstacle and update the scene -> Option C

5. Quick Check:

   Update planning scene with PlanningSceneInterface [OK]

Hint: Add obstacles via PlanningSceneInterface before planning [OK]

Common Mistakes:

• Trying to avoid obstacles by changing target pose only
• Restarting nodes unnecessarily
• Using RViz manual moves instead of programmatic updates