7-DOF Robotic Arm Motion Planning Algorithm Development for Humanoid Robots

Project Overview

Core Objective: Develop motion planning algorithms for Xiaomi’s 7-DOF humanoid robotic arm, enhancing motion precision (<0.3mm error), stability, and robustness against payload variations.
Technical Framework:

• Theoretical Basis: DH parameters, inverse kinematics (IK), trajectory interpolation
• Toolchain: MuJoCo simulation, C/Python co-development
• Validation Protocol: Dual verification system complying with ISO 9283 standards (positioning accuracy, path repeatability)

Key Technical Achievements

1. Kinematics Algorithm Development
   • Forward Kinematics: Established DH-based coordinate transformation model with 0.1mm calculation precision
   • IK Solver Optimization:
     • Developed universal inverse kinematics interface auto-adapting to URDF configurations
     • Hybrid numerical-geometric solution reducing end-effector positioning error to 0.3mm
   • Trajectory Smoothing: Implemented Kalman filtering with B-spline interpolation, decreasing joint velocity fluctuations by 30%
2. Simulation-Physical Validation
   • MuJoCo Environment: Calibrated dynamic parameters (gravity compensation, joint friction models) matching h1_2 hardware specs
   • Hardware-in-the-Loop Validation: <1.5% deviation in 50 test trajectories between simulation and physical tests

trajetory planner with filter

enduable test results demo

System Optimization

Three-Core Enhancement Strategy:

1. Fail-Safe Mechanism: Collision detection triggering 10ms emergency stop
2. Computational Efficiency: optimized code achieving 1kHz control frequency

Strategic Recommendations:

1. Engineering: Implement fault injection testing for failure mode analysis
2. Collaboration: Establish knowledge-sharing platform for URDF optimization