TOCALib: Optimal control library with interpolation for bimanual manipulation and obstacles avoidance

2025-04-10

AI Summary

Conventional trajectory planning for dual-arm robotic manipulation suffers from insufficient safety guarantees, limited real-time performance, and poor generalizability across tasks and platforms. Method: This work proposes a novel method for constructing an optimal trajectory library that jointly incorporates dynamic constraints and real-time collision avoidance. We integrate DCOL—a symbolic, differentiable collision detection algorithm—into the gradient-based optimization framework FROST, enabling end-to-end co-optimization of kinematic, dynamic, and collision constraints. A lightweight trajectory library is then generated via interpolation to support cross-platform deployment and machine learning data provisioning. Results: Experimental validation on the Mobile ALOHA platform demonstrates significant improvements in both safety and real-time performance for complex dual-arm tasks—including cooperative grasping and dynamic obstacle avoidance. The approach further exhibits strong extensibility to other multi-body systems, such as bipedal robots.

Technology Category

• Intelligent Robots: Motion and Path Planning
• Planning, Routing, and Scheduling: Replanning and Plan Repair
• Search and Optimization: Sampling/Simulation-based Search

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

The paper presents a new approach for constructing a library of optimal trajectories for two robotic manipulators, Two-Arm Optimal Control and Avoidance Library (TOCALib). The optimisation takes into account kinodynamic and other constraints within the FROST framework. The novelty of the method lies in the consideration of collisions using the DCOL method, which allows obtaining symbolic expressions for assessing the presence of collisions and using them in gradient-based optimization control methods. The proposed approach allowed the implementation of complex bimanual manipulations. In this paper we used Mobile Aloha as an example of TOCALib application. The approach can be extended to other bimanual robots, as well as to gait control of bipedal robots. It can also be used to construct training data for machine learning tasks for manipulation.

Problem

• Optimizing trajectories for two robotic manipulators with constraints
• Avoiding collisions using symbolic expressions in optimization
• Extending method to bimanual robots and bipedal gait control

Innovation

• Optimal trajectory library for bimanual robots
• Collision avoidance using symbolic DCOL method
• Integration with FROST framework for constraints