Computational Intelligence applied to Motion Planning and Control in Biped Robotics: A survey Juan J. Figueredo
Structure 1. Introduction 2. Dynamical and Biological Aspects of BipedWalking 3. Problem Definition 4. A taxonomy of motion planning and control methods in biped walking 5. Discussion and future trends
Motion planning and control is relevant because:
environments are devised to adapt well to humans.
It gives us understanding of human morphology, mechanics and control.
It is a complex control problem in nonlinear and nonholonomic systems.
Biomechanical Preliminaries of Walking
motion of several rigid bodies
Simplification to 12-DOF in lower limbs.
In the hip: Flexion-Extension, Abduction-Adduction, ExternalInternal Rotation In the knee: Flexion-Extension In the ankle: Plantarflexion-Dorsiflexion, PronationSupination
Biological Considerations on Biped Locomotion
Six models of bipedal walking (Vaughan):
walking as an evolutionary adaptation of hominids.
Minimization of energy consumption by displacing the CoM along an optimal path
Progressive learning with risk of falling minimization
Spinal cord interneurons acting as rhythmic central pattern generators
Neural system training along with biomechanical system and environment adaptation
Feedback control in powered dynamic locomotion
Biological Considerations on Biped Locomotion (II)
Tree levels for neural motion control: Feedback control in motoneurons: contribution of reflex action over motoneuron signal intensity. Feedback control in central pattern generator flexor-extensor centers: movement synchronization and reflex response to perturbation and loads. Higher level control: conscious control of locomotion..
Give to a biped robot an optimal locomotion
Walk conserving dynamic stability
Locally minimize energy consumption in locomotion
React to external perturbations
Plan gait trajectories to attain specific objectives
Move across unstructured environments
Globally minimize energy consumption in locomotion for a given objective
A taxonomy of motion planning and control methods in biped walking
Central Pattern Generator (CPG) Methods
Coordinated rhythmic stimulation to generate a gait pattern. It is inspired from the spinal motor center find in animals. Approaches:
Oscillatory Neural Networks
Evolutionary Optimization of CPGs
Rhythmical Dynamic Systems
Trajectory Tracking Methods Generating a kinematic pattern in a way such that following it (in joint spaced) yields a successful gait pattern. Advances in energy consumption optimization. Approaches:
Dynamic Walking Control
Obtain dynamic stable walking by a control based on various techniques. Highly complex. ZMP related. Partial objective tracking and phase reset techniques. Approaches:
Static Walking Control
Displaced by Dynamic Control Very low velocities required to make negligible the inertial forces. They still have a research value in studying the stationary phases and posture of bipeds and some specific movement patterns. Approaches:
Discussion and future trends
Current development in the field of biped robotics is highly varied Several objectives cannot be completely fulfilled be one method alone Active control
Cannot perform well in unstructured environments Passive Dynamic Walking
High efficiencies but cannot navigate satisfactorily in 2D and 3D Computational Intelligence
In early development
Low energy consumption