Dynamics And Motion Planning Of Lower Extremity Exoskeleton

Exoskeleton is an anthropomorphic mechanical system for being worn on human’s body parallel to the lateral side to enhance the wearer’s strength and endurance, exoskeleton detects in real time its own posture and the wearer’s movement intention through gyroscope, joint potentiometers or encoders, human-machine interaction sensors and plantar force sensors, and then, drives each joint to move in coordination with the wearer via the actuators such as electric motor or hydraulic cylinder. Wearer issues the movement intention and maintains the movement stability, exoskeleton follows the wearer in coordination and bears the load, in this way, the humans’ intelligence and the machine’s physical power could be integrated.At present, exoskeleton has many practical applications, for example, in the field of the aged and the disabled assistance, exoskeleton can be used to help the elderly and the disabled people finish the daily activities such as walking and climbing up stairs, to improve their quality of life; in the field of medical treatment, exoskeleton can assist the medical staff to conduct rehabilitation training on the patients of stroke or lower limb injury with higher precision and higher repeatability, on the one hand, this assistance can greatly reduce the work intensity of the medical staff, on the other hand, the control strategy can be adjusted to adapt the different training mode for the patients with different recovery; in the field of load carrying and individual soldier system, exoskeleton can help workers or soldiers march in high speed with bearing more materials such as communication equipments, construction equipments and weapons, and can reduce the human resource losses caused by injuries or non-combat loss of members which were due to huge body energy consumption.The aim of research in this dissertation is to develop a lower extremity exoskeleton to assist the load-bearing workers such as soldiers and rescuers to walk, squat down, stand up, climb up or down stairs. Firstly, the exoskeleton could be put on or taken off conveniently; secondly, the number of sensors should be decreased as far as possible to reduce the system complexity and no sensor could be allowed to set or pasted on the wearer’s body; the last, the exoskeleton should be insensitive to wear’s body size. To achieve these research goals, this dissertation did the studies in the following five aspects:1. The human lower extremity kinematics based on anthropometry theory is analyzed. The experiments of walking with different speeds or different loads, climbing up stairs, squatting down and standing up are conducted on the optoelectronic motion-capture system which is based on spatial position capture and three-dimensional reconstruction of the markers, and the kinematics of human’s lower extremity joints in the common gaits mentioned above are summarized by the experimental data.2. On the basis of analysis of human lower extremity kinematics, the DoFs of each joint of the exoskeleton are configured to meet the requirements of the common gaits, and the mechanical structure of the exoskeleton (with no actuators) is designed. Then, D-H kinematic model of the exoskeleton is built and the human-machine connection positions are determined via the kinematic analyses.3. By comparing the typical exoskeleton dynamic model, a "two-state" dynamic model of the exoskeleton is put forward, in which, the dynamic model of the exoskeleton is divided into two states:NSP (No Swing leg Phase) and CSP (Containing Swing leg Phase), and the dynamic models of these two states are established via the D ’Alembert-Lagrange Equation. On the basis of the dynamic models, the control system could obtain the segment inertia forces, plantar forces and ZMP only on the detection of exoskeleton’s joint angles, this merit could help effectively reduce the number of sensors. In addition, the actively actuated DoF between the stance foot toe and the ground is eliminated in the dynamic models, and the correctness of the dynamic models is verified by the use of MATLAB and Adams. At last, the exoskeleton dynamic analyses of walking with different speeds or different loads, climbing up stairs, squatting down and standing up are carried out.4. Based on dynamic analyses of the exoskeleton, the actuating characteristics of each joint of the exoskeleton are summarized, then, the integrated hydraulic-tendon sheath actuators are configured and optimized on each actively actuated DoFs of the exoskeleton’s joints, and the springs with detailed design and calculation are configured on each passively actuated DoFs. Finally, strength check on the key part of the exoskeleton including driving systems is conducted to ensure the structural safety.5. By analyzing the typical exoskeleton control strategies, inverse kinematics motion planning based on the human-machine posture error at ankle joint and PD control based on dynamic model is put forward for the swing leg control, and fuzzy motion planning based on the error between CoP of the wearer’s plantar force and ZMP of the exoskeleton is for the stance leg control. The control system identifies the gait stages of each leg through the fuzzy algorithm and the detection of plantar forces, and then chooses the corresponding control strategies to stance leg and swing leg. The sensor system is designed and calibrated, including torso posture sensor, joint potentiometers, human-machine interaction sensor at ankle joint and plantar force detecting soles. At last, the swing leg motion control experiments and the stance leg motion planning are carried out respectively.