Executing Held Object Motion logo

Executing Held Object Motion

Organization
graph-robots
executing-held-object-motion

Executes an ordered, collision-aware pose sequence for an already-grasped rigid object without releasing it - the escape from support, clear-space rotation, fixture transit and orientation-locked local legs of a carry plan, or only the free-space approach waypoint of a placement plan. Use when a held object must be carried or reoriented before insertion, mating, packing, or sorting, and use executing-feature-mating afterwards for the engagement and release.

Overview

Publishergraph-robots
Repositoryopen-robot-skills
Skill nameexecuting-held-object-motion
Stars
58
Forks
8
Bundled files
2
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by graph-robots on GitHub. Read the source before you install it.

Installation

Install the Executing Held Object Motion AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/graph-robots/open-robot-skills/tree/main/skills/executing-held-object-motion
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/graph-robots/open-robot-skills.git /tmp/open-robot-skills
mkdir -p .claude/skills
cp -r /tmp/open-robot-skills/skills/executing-held-object-motion .claude/skills/executing-held-object-motion
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Executing Held Object Motion in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Executing Held Object Motion on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Executing Held Object Motion is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Both scripts also return a per-waypoint report (waypoint_reports, waypoint_report), stated here because the type registry names no bare list or record. An execution_profile (one per object kind) adds speed_scale, a Cartesian fallback when the planner refuses, and -- for the approach -- a local Cartesian shortcut and a goal-contact retry; robot.get_ee_pose is read only under a profile (execute_approach_only) or measure_errors (execute_reorientation), because the read is a recorded tool call. arm_id names the hand on a bimanual cell and is absent from every call when unset.

executing-held-object-motion

Execute motion for a rigid object that is already held. The skill preserves the grasp: it does not open or close the gripper. Its input is an ordered PoseSequence containing clearance, transit, and orientation poses.

When to use

  • Stand an elongated object upright before putting it through an opening.
  • Turn a tool from a table grasp into a hanging or fixture-mating orientation.
  • Align a keyed object before insertion.
  • Reorient an item before constrained packing or sorting.
  • Reach only the approach pose of a placement plan so the held object can be re-observed (wrist re-registration) before a tight engagement.

Do not use it for an ordinary bin drop when transporting-objects can lift, translate, descend, and release directly.

Recommended subgraphs

text
execute_reorientation -> reoriented
execute_approach_only -> reached

execute_reorientation runs the canonical script with reorientation_plan = Ref("in.reorientation_plan"). Each waypoint is a typed record {pose, mode, use_attachment?, max_attempts?, allow_start_contact?, allow_goal_contact?, contact_margin?}. It forwards the plan's world_config and attached_object to every planned leg and never replaces a rejected collision-aware plan with an unchecked move. Use contact_transition only for the initial support escape (a plain Cartesian move); use planned_joint for clear-space rotation/transit and planned_linear for an orientation-locked straight leg. A plan-level time_scale > 1 slows execution by resampling the joint path; every planned leg is executed with a 60-step-per-waypoint budget so a stuck waypoint does not stall the graph. Output: final_pose: Se3Pose, the last waypoint's end-effector pose.

execute_approach_only takes placement_plan: PoseSequence (the plan that executing-feature-mating will finish) and executes only its first waypoint as a collision-aware motion.plan_to_pose leg with the plan's world and attachment, retrying the sampled planner up to three times and tracking the trajectory to 2 mm. It raises when the planner refuses (route to blocked). Output: approach_pose: Se3Pose, the waypoint it reached, so the graph can re-register the held object there and recompute the engagement.

Boundaries

  • Upstream geometry or perception determines the desired object orientation and sufficient clearance. This skill executes that typed request.
  • The sequence must describe end-effector poses, not object poses.
  • The skill never releases the object and never queries cameras, simulation state, task goals, evaluators, or reward.
  • Full 3-DOF orientation changes require a robot IK backend that honors wrist roll. A position/approach-axis-only backend cannot reliably stand a syringe or long tool upright.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Executing Held Object Motion AI skill do?

Executes an ordered, collision-aware pose sequence for an already-grasped rigid object without releasing it - the escape from support, clear-space rotation, fixture transit and orientation-locked local legs of a carry plan, or only the free-space approach waypoint of a placement plan. Use when a held object must be carried or reoriented before insertion, mating, packing, or sorting, and use executing-feature-mating afterwards for the engagement and release.

Why use Executing Held Object Motion on TypingMind?

Because you install it once and use it with any model. Executing Held Object Motion is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Executing Held Object Motion in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/graph-robots/open-robot-skills/tree/main/skills/executing-held-object-motion. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Executing Held Object Motion?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Executing Held Object Motion?

As many as you like. As long as a model supports skills, you can use Executing Held Object Motion with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Executing Held Object Motion AI skill free?

Yes. It is published on GitHub by graph-robots under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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