[Paper Review] Automatic Design of Task-specific Robotic Arms

Ruta Desai, Margarita Safonova+2 more|arXiv (Cornell University)|Jun 19, 2018

Robotic Mechanisms and Dynamics3 references3 citations

TL;DR

This paper presents an interactive, search-based system that automatically designs task-specific robotic arms from modular parts using high-level motion trajectories as input. By formulating design as an A*-search problem guided by inverse kinematics error heuristics, the system generates minimal, functional arms that track user-specified end-effector paths, demonstrating simpler designs than manually created counterparts in simulation.

ABSTRACT

We present an interactive, computational design system for creating custom robotic arms given high-level task descriptions and environmental constraints. Various task requirements can be encoded as desired motion trajectories for the robot arm's end-effector. Given such end-effector trajectories, our system enables on-demand design of custom robot arms using a library of modular and reconfigurable parts such as actuators and connecting links. By searching through the combinatorial set of possible arrangements of these parts, our method generates a functional, as-simple-as-possible robot arm that is capable of tracking the desired trajectories. We demonstrate our system's capabilities by creating robot arm designs in simulation, for various trajectory following scenarios.

Motivation & Objective

• To enable rapid, automatic synthesis of custom robotic arms tailored to specific tasks using modular components.
• To address the limitation of fixed, non-reconfigurable commercial robotic arms in specialized, constrained environments.
• To reduce design time and complexity by generating the simplest possible arm that achieves a desired motion trajectory.
• To support interactive, user-driven design through a physics-based simulation interface for task specification.
• To validate the approach by comparing automatically generated designs to manually created ones, showing improved simplicity in some cases.

Proposed method

• The system models robotic arms as assemblies of modular parts (actuators, links, bases, end-effectors) connected via a defined abstraction for structural representation.
• It formulates the design process as an A* search through the space of possible configurations, guided by a heuristic based on inverse kinematics (IK) error.
• The heuristic function estimates the cost to reach a goal trajectory by computing the cumulative IK error across trajectory frames, ensuring admissibility through a virtual end-effector for intermediate nodes.
• A virtual end-effector is introduced to maintain compatibility across all intermediate designs, enabling consistent heuristic evaluation without overestimating costs.
• The system uses a physics-based simulation environment to validate designs and allow users to define tasks with obstacles and target trajectories.
• Designs are generated by searching for the minimal configuration (fewest DOF) that achieves the desired trajectory with acceptable IK error.

Experimental results

Research questions

• RQ1 Can a computational system automatically generate minimal, functional robotic arm designs from modular parts based on high-level motion trajectories?
• RQ2 How can an informed search strategy efficiently explore the combinatorial space of modular robotic arm configurations?
• RQ3 To what extent can the system outperform manually designed arms in terms of simplicity (fewer DOF) while maintaining trajectory accuracy?
• RQ4 How can admissible heuristics be constructed for design search when intermediate configurations may lack real end-effectors?
• RQ5 Can the system be extended to handle complex environments with obstacles and multiple task constraints?

Key findings

• The system successfully generated valid robotic arm designs for various trajectory-following tasks in simulation, with design times varying based on trajectory complexity and environmental constraints.
• In unconstrained environments, the system often produced simpler designs (fewer degrees of freedom) than the original manually created arms, demonstrating improved efficiency.
• The use of a virtual end-effector enabled admissible heuristic evaluation across all intermediate designs, ensuring optimal search performance.
• The A* search with IK error-based heuristics efficiently guided the exploration toward functional, minimal configurations without exhaustive enumeration.
• The interactive simulation interface allowed users to define tasks with obstacles and verify designs before physical fabrication.
• The approach demonstrated generality beyond robotic arms, suggesting applicability to other reconfigurable robotic systems.