Characterization of Constraints in Flexible Unknown Environments

2026-03-25

AI Summary

This work addresses the challenge of safe autonomous manipulation in unknown environments where prior knowledge of constraint types and stiffness is unavailable. The authors propose an online path-planning algorithm that simultaneously identifies constraint types, estimates their screw parameters, and constructs a global stiffness model by fusing force and pose feedback in real time during exploration. By integrating stiffness tensor analysis, eigenvector mapping, and a library of canonical constraint patterns—such as hinges and planar contacts—the method achieves, for the first time, real-time identification and characterization of common mechanical constraints without any prior information. Simulations and physical experiments demonstrate that the system accurately recognizes compliant constraints like flexible hinges, enabling safe human–robot collaboration in applications such as surgical organ retraction.

Technology Category

• Intelligent Robots: Manipulation
• Planning, Routing, and Scheduling: Replanning and Plan Repair
• Constraint Satisfaction and Optimization: Constraint Learning and Acquisition

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments

Abstract

This paper presents an online path planning algorithm for safe autonomous manipulation of a flexibly constrained object in an unknown environment. Methods for real time identification and characterization of perceived flexible constraints and global stiffness are presented. Used in tandem, these methods allow a robot to simultaneously explore, characterize, and manipulate an elastic system safely. Navigation without a-priori knowledge of the system is achieved using constraint exploration based on local force and position information. The perceived constraint stiffness is considered at multiple poses along an object's (system) trajectory. Using stiffness eigenvector information, global stiffness behavior is characterized and identified using an atlas of simple mechanical constraints, such as hinges and planar constraints. Validation of these algorithms is carried out by simulation and experimentally. The ability to recognize several common simple mechanical constraints (such as a flexible hinge) in real time, and to subsequently identify relevant screw parameters is demonstrated. These results suggest the feasibility of simultaneous global constrain/stiffness exploration and safe manipulation of flexibly constrained objects. We believe that this approach will eventually enable safe cooperative manipulation in applications such as organ retraction and manipulation during surgery

Problem

• flexible constraints
• unknown environments
• autonomous manipulation
• stiffness characterization
• constraint identification

Innovation

• flexible constraints
• online path planning
• stiffness characterization
• constraint identification
• screw parameters