Module 13: Full-Body Autonomy

Introduction

Full autonomy requires integrating all subsystems—perception, planning, control, and decision-making—into a coherent whole. This module covers system integration and autonomous operation.

Section 1: Autonomous Architecture

1.1 Perception-Action Loop

Autonomy: The capability of a system to make decisions and take actions without human intervention based on its perception of the environment and internal goals.

class AutonomousController:
    def __init__(self):
        self.perception = PerceptionModule()
        self.planner = HierarchicalPlanner()
        self.controller = WholeBodyController()

    def loop(self):
        while True:
            # Perceive
            world_state = self.perception.update()

            # Plan
            task = self.planner.get_current_task()
            motion_plan = self.planner.plan_motion(world_state, task)

            # Execute
            self.controller.execute(motion_plan)

1.2 State Estimation

Fusing all sensor data into coherent world model.

Section 2: Decision Making

2.1 Behavior Trees

Hierarchical task execution:

Root (Sequence)
├── Check Battery (Condition)
├── Locate Object (Action)
├── Navigate to Object (Action)
├── Pick Object (Action)
└── Deliver Object (Action)

2.2 Uncertainty Handling

Autonomous systems must handle sensor failures, unexpected obstacles, and task failures gracefully. Robust fallback behaviors are essential.

Section 3: Loco-Manipulation

3.1 Coordinated Movement

Simultaneous walking and manipulation:

$\ddot{\mathbf{q}} = \mathbf{M}^{-1}(\boldsymbol{\tau} - \mathbf{h} + \mathbf{J}_c^T\mathbf{f}_c)$

subject to:

Stability constraints
Manipulation task constraints
Joint limits

3.2 Mobile Manipulation Planning

Planning paths and grasps jointly.

Section 4: Long-Horizon Tasks

4.1 Task and Motion Planning (TAMP)

Combining symbolic and geometric planning.

4.2 Hierarchical Decomposition

Breaking complex tasks into manageable subtasks.

Summary

Key takeaways:

Autonomy requires tight integration of all subsystems
Behavior trees enable modular task specification
Loco-manipulation requires whole-body coordination
Long-horizon tasks need hierarchical planning

Key Concepts

Autonomy: Independent decision-making and action
Behavior Tree: Hierarchical task structure
Loco-Manipulation: Combined locomotion and manipulation
TAMP: Task and motion planning

Introduction​

Section 1: Autonomous Architecture​

1.1 Perception-Action Loop​

1.2 State Estimation​

Section 2: Decision Making​

2.1 Behavior Trees​

2.2 Uncertainty Handling​

Section 3: Loco-Manipulation​

3.1 Coordinated Movement​

3.2 Mobile Manipulation Planning​

Section 4: Long-Horizon Tasks​

4.1 Task and Motion Planning (TAMP)​

4.2 Hierarchical Decomposition​

Summary​

Key Concepts​

Further Reading​