robotics-design-patterns

Name: robotics-design-patterns
Author: arpitg1304

320stars44forks

How to install robotics-design-patterns?

arpitg1304/robotics-agent-skills/robotics-design-patterns

$npx -y skills add arpitg1304/robotics-agent-skills --skill robotics-design-patterns

Installs into the current project.

Summary

Architecture patterns, design principles, and proven recipes for building robust robotics software. Use this skill when designing robot software architectures, choosing between behavioral frameworks, structuring perception-planning-control pipelines, implementing state machines,

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SKILL.md

1	# Robotics Design Patterns
2
3	## When to Use This Skill
4	- Designing robot software architecture from scratch
5	- Choosing between behavior trees, FSMs, or hybrid approaches
6	- Structuring perception → planning → control pipelines
7	- Implementing safety systems and watchdogs
8	- Building hardware abstraction layers (HAL)
9	- Designing for sim-to-real transfer
10	- Architecting multi-robot / fleet systems
11	- Making real-time vs. non-real-time tradeoffs
12
13	## Pattern 1: The Robot Software Stack
14
15	Every robot system follows this layered architecture, regardless of complexity:
16
17	```
18	┌─────────────────────────────────────────────┐
19	│ APPLICATION LAYER │
20	│ Mission planning, task allocation, UI │
21	├─────────────────────────────────────────────┤
22	│ BEHAVIORAL LAYER │
23	│ Behavior trees, FSMs, decision-making │
24	├─────────────────────────────────────────────┤
25	│ FUNCTIONAL LAYER │
26	│ Perception, Planning, Control, Estimation │
27	├─────────────────────────────────────────────┤
28	│ COMMUNICATION LAYER │
29	│ ROS2, DDS, shared memory, IPC │
30	├─────────────────────────────────────────────┤
31	│ HARDWARE ABSTRACTION LAYER │
32	│ Drivers, sensor interfaces, actuators │
33	├─────────────────────────────────────────────┤
34	│ HARDWARE LAYER │
35	│ Cameras, LiDARs, motors, grippers, IMUs │
36	└─────────────────────────────────────────────┘
37	```
38
39	Design Rule: Information flows UP through perception, decisions flow DOWN through control. Never let the application layer directly command hardware.
40
41	## Pattern 2: Behavior Trees (BT)
42
43	Behavior trees are the recommended default for robot decision-making. They're modular, reusable, and easier to debug than FSMs for complex behaviors.
44
45	### Core Node Types
46
47	```
48	Sequence (→) : Execute children left-to-right, FAIL on first failure
49	Fallback (?) : Execute children left-to-right, SUCCEED on first success
50	Parallel (⇉) : Execute all children simultaneously
51	Decorator : Modify a single child's behavior
52	Action (leaf) : Execute a robot action
53	Condition (leaf) : Check a condition (no side effects)
54	```
55
56	### Example: Pick-and-Place BT
57
58	```
59	→ Sequence
60	/ \| \
61	→ Check → Pick → Place
62	/ \ / \| \ / \| \
63	Battery Obj Open Move Close Move Open Release
64	OK? Found? Grip To Grip To Grip
65	per Obj per Goal per
66	```
67
68	### Implementation Pattern
69
70	```python
71	import py_trees
72
73	class MoveToTarget(py_trees.behaviour.Behaviour):
74	"""Action node: Move robot to a target pose"""
75
76	def __init__(self, name, target_key="target_pose"):
77	super().__init__(name)
78	self.target_key = target_key
79	self.action_client = None
80
81	def setup(self, **kwargs):
82	"""Called once when tree is set up — initialize resources"""
83	self.node = kwargs.get('node') # ROS2 node
84	self.action_client = ActionClient(
85	self.node, MoveBase, 'move_base')
86
87	def initialise(self):
88	"""Called when this node first ticks — send the goal"""
89	bb = self.blackboard
90	target = bb.get(self.target_key)
91	self.goal_handle = self.action_client.send_goal(target)
92	self.logger.info(f"Moving to {target}")
93
94	def update(self):
95	"""Called every tick — check progress"""
96	if self.goal_handle is None:
97	return py_trees.common.Status.FAILURE
98
99	status = self.goal_handle.status
100	if status == GoalStatus.STATUS_SUCCEEDED:
101	return py_trees.common.Status.SUCCESS
102	elif status == GoalStatus.STATUS_ABORTED:
103	return py_trees.common.Status.FAILURE
104	else:
105	return py_trees.common.Status.RUNNING
106
107	def terminate(self, new_status):
108	"""Called when node exits — cancel if preempted"""
109	if new_status == py_trees.common.Status.INVALID:
110	if self.goal_handle:
111	self.goal_handle.cancel_goal()
112	self.logger.info("Movement cancelled")
113
114	# Build the tree
115	def create_pick_place_tree():
116	root = py_trees.composites.Sequence("P

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robotics-design-patterns

320stars44forks

View on GitHub

How to install robotics-design-patterns?

arpitg1304/robotics-agent-skills/robotics-design-patterns

$npx -y skills add arpitg1304/robotics-agent-skills --skill robotics-design-patterns

Installs into the current project.

Summary

Files · 1

View on GitHub

SKILL.md

1	# Robotics Design Patterns
2
3	## When to Use This Skill
4	- Designing robot software architecture from scratch
5	- Choosing between behavior trees, FSMs, or hybrid approaches
6	- Structuring perception → planning → control pipelines
7	- Implementing safety systems and watchdogs
8	- Building hardware abstraction layers (HAL)
9	- Designing for sim-to-real transfer
10	- Architecting multi-robot / fleet systems
11	- Making real-time vs. non-real-time tradeoffs
12
13	## Pattern 1: The Robot Software Stack
14
15	Every robot system follows this layered architecture, regardless of complexity:
16
17	```
18	┌─────────────────────────────────────────────┐
19	│ APPLICATION LAYER │
20	│ Mission planning, task allocation, UI │
21	├─────────────────────────────────────────────┤
22	│ BEHAVIORAL LAYER │
23	│ Behavior trees, FSMs, decision-making │
24	├─────────────────────────────────────────────┤
25	│ FUNCTIONAL LAYER │
26	│ Perception, Planning, Control, Estimation │
27	├─────────────────────────────────────────────┤
28	│ COMMUNICATION LAYER │
29	│ ROS2, DDS, shared memory, IPC │
30	├─────────────────────────────────────────────┤
31	│ HARDWARE ABSTRACTION LAYER │
32	│ Drivers, sensor interfaces, actuators │
33	├─────────────────────────────────────────────┤
34	│ HARDWARE LAYER │
35	│ Cameras, LiDARs, motors, grippers, IMUs │
36	└─────────────────────────────────────────────┘
37	```
38
39	Design Rule: Information flows UP through perception, decisions flow DOWN through control. Never let the application layer directly command hardware.
40
41	## Pattern 2: Behavior Trees (BT)
42
43	Behavior trees are the recommended default for robot decision-making. They're modular, reusable, and easier to debug than FSMs for complex behaviors.
44
45	### Core Node Types
46
47	```
48	Sequence (→) : Execute children left-to-right, FAIL on first failure
49	Fallback (?) : Execute children left-to-right, SUCCEED on first success
50	Parallel (⇉) : Execute all children simultaneously
51	Decorator : Modify a single child's behavior
52	Action (leaf) : Execute a robot action
53	Condition (leaf) : Check a condition (no side effects)
54	```
55
56	### Example: Pick-and-Place BT
57
58	```
59	→ Sequence
60	/ \| \
61	→ Check → Pick → Place
62	/ \ / \| \ / \| \
63	Battery Obj Open Move Close Move Open Release
64	OK? Found? Grip To Grip To Grip
65	per Obj per Goal per
66	```
67
68	### Implementation Pattern
69
70	```python
71	import py_trees
72
73	class MoveToTarget(py_trees.behaviour.Behaviour):
74	"""Action node: Move robot to a target pose"""
75
76	def __init__(self, name, target_key="target_pose"):
77	super().__init__(name)
78	self.target_key = target_key
79	self.action_client = None
80
81	def setup(self, **kwargs):
82	"""Called once when tree is set up — initialize resources"""
83	self.node = kwargs.get('node') # ROS2 node
84	self.action_client = ActionClient(
85	self.node, MoveBase, 'move_base')
86
87	def initialise(self):
88	"""Called when this node first ticks — send the goal"""
89	bb = self.blackboard
90	target = bb.get(self.target_key)
91	self.goal_handle = self.action_client.send_goal(target)
92	self.logger.info(f"Moving to {target}")
93
94	def update(self):
95	"""Called every tick — check progress"""
96	if self.goal_handle is None:
97	return py_trees.common.Status.FAILURE
98
99	status = self.goal_handle.status
100	if status == GoalStatus.STATUS_SUCCEEDED:
101	return py_trees.common.Status.SUCCESS
102	elif status == GoalStatus.STATUS_ABORTED:
103	return py_trees.common.Status.FAILURE
104	else:
105	return py_trees.common.Status.RUNNING
106
107	def terminate(self, new_status):
108	"""Called when node exits — cancel if preempted"""
109	if new_status == py_trees.common.Status.INVALID:
110	if self.goal_handle:
111	self.goal_handle.cancel_goal()
112	self.logger.info("Movement cancelled")
113
114	# Build the tree
115	def create_pick_place_tree():
116	root = py_trees.composites.Sequence("P

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