strands-spot 0.1.0

Generic tool for Boston Dynamics Spot SDK for Strands Agents

Strands Spot

Boston Dynamics Spot Control for Strands Agents

Strands Docs ◆ Spot SDK Docs ◆ Spot SDK GitHub

A Python tool for controlling Boston Dynamics Spot robots through the Strands Agents framework.

Call Spot SDK services and methods directly without writing boilerplate connection code:

use_spot(service="robot_command", method="stand")
use_spot(service="image", method="get_image_from_sources") 
use_spot(service="power", method="power_on")

Works with natural language when used with Strands agents:

agent = Agent(tools=[use_spot])
agent("Make Spot stand up and take a picture")

How It Works

You specify which Spot SDK service and method to call. The tool handles connections, authentication, and lease management:

use_spot(
    service="robot_command",    # Which SDK service
    method="stand",              # Which method to call
    params={}                    # Method parameters
)

This maps to Spot SDK: service="robot_command" → RobotCommandClient, method="stand" → synchro_stand_command()

Installation

pip install strands-spot

Dependencies:

pip install bosdyn-client bosdyn-api bosdyn-core  # Required
pip install strands-agents  # Optional, for natural language

Environment setup:

export SPOT_HOSTNAME="192.168.80.3"
export SPOT_USERNAME="admin"
export SPOT_PASSWORD="password"

Usage

from strands_spot import use_spot

# Stand the robot
use_spot(
    hostname="192.168.80.3",
    service="robot_command",
    method="stand"
)

# Capture image
use_spot(
    hostname="192.168.80.3",
    service="image",
    method="get_image_from_sources",
    params={"image_sources": ["frontleft_fisheye_image"]}
)

# With natural language
from strands import Agent
agent = Agent(tools=[use_spot])
agent("Make Spot stand and take a picture")

Available Services

Service	Client	Common Methods	Description
robot_command	RobotCommandClient	stand, sit, velocity_command, self_right	Motion control and poses
robot_state	RobotStateClient	get_robot_state, get_robot_metrics, get_robot_hardware_configuration	Query robot status
power	PowerClient	power_on, power_off, power_cycle_robot	Power management
image	ImageClient	list_image_sources, get_image_from_sources	Camera capture
graph_nav	GraphNavClient	navigate_to, upload_graph, set_localization	Autonomous navigation
manipulation	ManipulationApiClient	manipulation_api_command, grasp_override	Arm control
docking	DockingClient	docking_command, get_docking_config	Charging station docking
lease	LeaseClient	acquire, release, list_leases	Resource management
estop	EstopClient	register, deregister, set_status	Emergency stop
time_sync	TimeSyncClient	get_robot_time_range, update	Clock synchronization
directory	DirectoryClient	list, get_entry	Service discovery
choreography	ChoreographyClient	execute_choreography, list_all_moves	Dance routines
data_acquisition	DataAcquisitionClient	acquire_data, list_capture_actions	Sensor data collection
autowalk	AutowalkClient	load_autowalk, compile_autowalk	Mission playback
spot_check	SpotCheckClient	start_spot_check, spot_check_feedback	Robot diagnostics

💡 100+ Methods Available

Each service exposes 5-20 methods. Examples:

robot_command (Motion Control):

• stand, sit, self_right, safe_power_off
• velocity_command, trajectory_command
• arm_stow, arm_ready, gripper_command
• stance_command, follow_arm_command

robot_state (Status Queries):

• get_robot_state, get_robot_metrics
• get_robot_hardware_configuration
• get_hardware_status_streaming

image (Vision):

• list_image_sources, get_image_from_sources
• build_image_request, decode_image

graph_nav (Navigation):

• navigate_to, navigate_route, navigate_to_anchor
• upload_graph, download_graph
• set_localization, get_localization_state
• clear_graph, get_status

See Spot SDK Python Client Reference for complete method documentation.

Features

Automatic lease management - Leases are acquired and released automatically

Vision model integration - Captured images are formatted for LLM vision models to analyze

All SDK parameters exposed - Full access to Spot SDK without limitations

# Images captured from Spot can be analyzed by vision models
agent = Agent(tools=[use_spot])
agent("Take a picture and describe what you see")

Examples

Complete Workflow: Power → Stand → Capture → Sit → Power Off

from strands_spot import use_spot

hostname = "192.168.80.3"
username = "admin"
password = "password"

# 1. Power on motors
use_spot(
    hostname=hostname, username=username, password=password,
    service="power", method="power_on", params={"timeout_sec": 20}
)

# 2. Stand up
use_spot(
    hostname=hostname, username=username, password=password,
    service="robot_command", method="stand", params={}
)

# 3. Capture image from front-left camera
result = use_spot(
    hostname=hostname, username=username, password=password,
    service="image", method="get_image_from_sources",
    params={"image_sources": ["frontleft_fisheye_image"]}
)

# 4. Sit down
use_spot(
    hostname=hostname, username=username, password=password,
    service="robot_command", method="sit", params={}
)

# 5. Power off
use_spot(
    hostname=hostname, username=username, password=password,
    service="power", method="power_off",
    params={"cut_immediately": False, "timeout_sec": 20}
)

Velocity Control (Walking)

import time

# Walk forward at 0.5 m/s
use_spot(
    service="robot_command",
    method="velocity_command",
    params={"v_x": 0.5, "v_y": 0.0, "v_rot": 0.0}
)
time.sleep(3)  # Walk for 3 seconds

# Turn in place at 0.3 rad/s
use_spot(
    service="robot_command",
    method="velocity_command",
    params={"v_x": 0.0, "v_y": 0.0, "v_rot": 0.3}
)
time.sleep(2)  # Turn for 2 seconds

# Stop
use_spot(
    service="robot_command",
    method="velocity_command",
    params={"v_x": 0.0, "v_y": 0.0, "v_rot": 0.0}
)

Arm Manipulation

# Unstow the arm
use_spot(service="robot_command", method="arm_ready", params={})

# Move arm to position (Cartesian command)
use_spot(
    service="manipulation",
    method="manipulation_api_command",
    params={
        "arm_cartesian_command": {
            "pose": {
                "position": {"x": 0.8, "y": 0.0, "z": 0.25},
                "rotation": {"w": 1, "x": 0, "y": 0, "z": 0}
            }
        }
    }
)

# Close gripper
use_spot(
    service="robot_command",
    method="gripper_command",
    params={
        "claw_gripper_command": {
            "trajectory": {"position": 0.0}  # 0.0 = fully closed
        }
    }
)

# Stow the arm
use_spot(service="robot_command", method="arm_stow", params={})

Multi-Camera Capture

# List all available cameras
result = use_spot(service="image", method="list_image_sources", params={})
print(result["content"][1]["json"]["response_data"]["image_sources"])

# Capture from multiple cameras simultaneously
result = use_spot(
    service="image",
    method="get_image_from_sources",
    params={
        "image_sources": [
            "frontleft_fisheye_image",
            "frontright_fisheye_image",
            "hand_color_image"
        ]
    }
)

# Images are automatically formatted for LLM consumption!
# The response content contains image blocks that the LLM can "see"
# Content structure:
# [
#   {"text": "✅ Executed image.get_image_from_sources - captured 3 image(s)"},
#   {"image": {"format": "jpeg", "source": {"bytes": <image1_bytes>}}},
#   {"image": {"format": "jpeg", "source": {"bytes": <image2_bytes>}}},
#   {"image": {"format": "jpeg", "source": {"bytes": <image3_bytes>}}},
#   {"json": {"response_data": {...}}},
#   {"json": {"metadata": {...}}}
# ]

# To save images manually (optional):
for i, content_block in enumerate(result["content"]):
    if "image" in content_block:
        image_bytes = content_block["image"]["source"]["bytes"]
        with open(f"spot_image_{i}.jpg", "wb") as f:
            f.write(image_bytes)
        print(f"Saved spot_image_{i}.jpg")

Natural Language Control

from strands import Agent
from strands_spot import use_spot

agent = Agent(tools=[use_spot])

# Agent interprets and executes
agent("""
Connect to Spot robot at 192.168.80.3 with admin credentials.
First, check the robot's battery level.
If battery is above 20%, make the robot stand up and wave.
Then capture images from all cameras and sit back down.
""")

# The agent will break this into atomic use_spot calls:
# 1. use_spot(service="robot_state", method="get_robot_state", ...)
# 2. use_spot(service="robot_command", method="stand", ...)
# 3. use_spot(service="robot_command", method="arm_ready", ...)
# 4. use_spot(service="image", method="get_image_from_sources", ...)
# 5. use_spot(service="robot_command", method="sit", ...)

Vision-Enabled Agent (LLM Can See!)

from strands import Agent
from strands_spot import use_spot

agent = Agent(tools=[use_spot])

# The agent can capture AND analyze images
response = agent("""
Connect to Spot at 192.168.80.3.
Take a picture from the front-left camera and tell me:
1. What objects do you see?
2. Is the path ahead clear?
3. Are there any obstacles?
""")

# Behind the scenes:
# 1. Agent calls use_spot(service="image", method="get_image_from_sources")
# 2. Tool returns image in LLM-readable format
# 3. Agent's vision model analyzes the image
# 4. Agent provides natural language response with image analysis

print(response)
# Output: "I can see a hallway with clear flooring. There's a door on the left
#          and some office furniture on the right. The path ahead is clear with
#          no obstacles detected within 5 meters."

Real-World Scenario: Autonomous Inspection

agent = Agent(tools=[use_spot])

# Complex multi-step task with vision
agent("""
Using Spot robot at 192.168.80.3:

1. Stand up and check battery level
2. Walk forward 2 meters
3. Capture images from all 5 cameras
4. Analyze the images and report:
   - Any equipment damage visible
   - Temperature gauge readings (if visible)
   - Safety hazards
5. Walk back 2 meters
6. Sit down and power off

Report your findings in a structured format.
""")

# The agent autonomously:
# - Plans the sequence of SDK calls
# - Executes motion commands
# - Captures multiple camera views
# - Analyzes visual data with vision models
# - Generates comprehensive inspection report

Safety

Before operating:

• Clear 3m around robot
• Keep E-stop accessible
• Verify Spot firmware compatibility (SDK 5.0+)

During operation:

# Check robot state before commands
state = use_spot(service="robot_state", method="get_robot_state")

# Use timeouts to prevent hanging
use_spot(service="power", method="power_on", params={"timeout_sec": 20})

# Emergency stop
use_spot(service="robot_command", method="velocity_command",
         params={"v_x": 0.0, "v_y": 0.0, "v_rot": 0.0})

License

Apache-2.0

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GitHub ◆ Spot SDK Docs ◆ Strands Docs