Lecture

Modeling Human Motor Skills: Enhancing Motion Planning

Graph Chat

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Description

This lecture explores the modeling of human motor skills to improve human-like motion planning in robotics. It covers recent advancements in robotic design, the use of functional Principal Component Analysis, and the development of a novel solution to overcome limitations in anthropomorphic manipulators. The lecture also discusses the planning process via functional Principal Components, problem formalization for human-like movements, and the implementation of trajectories in joint space. Additionally, it delves into obstacle avoidance, Cartesian impedance control, and the control law for end effectors. The lecture concludes with a focus on achieving accurate motion tracking and error minimization in various motion scenarios.

Official source

Related concepts (11)

Motion planning

Motion planning, also path planning (also known as the navigation problem or the piano mover's problem) is a computational problem to find a sequence of valid configurations that moves the object from the source to destination. The term is used in computational geometry, computer animation, robotics and computer games. For example, consider navigating a mobile robot inside a building to a distant waypoint. It should execute this task while avoiding walls and not falling down stairs.

Robotics

Robotics is an interdisciplinary branch of electronics and communication, computer science and engineering. Robotics involves the design, construction, operation, and use of robots. The goal of robotics is to design machines that can help and assist humans. Robotics integrates fields of mechanical engineering, electrical engineering, information engineering, mechatronics engineering, electronics, biomedical engineering, computer engineering, control systems engineering, software engineering, mathematics, etc.

Motor skill

A motor skill is a function that involves specific movements of the body's muscles to perform a certain task. These tasks could include walking, running, or riding a bike. In order to perform this skill, the body's nervous system, muscles, and brain have to all work together. The goal of motor skill is to optimize the ability to perform the skill at the rate of success, precision, and to reduce the energy consumption required for performance. Performance is an act of executing a motor skill or task.

Soft robotics

Soft robotics is a subfield of robotics that concerns the design, control, and fabrication of robots composed of compliant materials, instead of rigid links. In contrast to rigid-bodied robots built from metals, ceramics and hard plastics, the compliance of soft robots can improve their safety when working in close contact with humans. The goal of soft robotics is the design and construction of robots with physically flexible bodies and electronics. Sometimes softness is limited to part of the machine.

Robot

A robot is a machine—especially one programmable by a computer—capable of carrying out a complex series of actions automatically. A robot can be guided by an external control device, or the control may be embedded within. Robots may be constructed to evoke human form, but most robots are task-performing machines, designed with an emphasis on stark functionality, rather than expressive aesthetics.

Related lectures (32)

Interpersonal Manual Tasks: Human-Robot Interactions

Delves into human-robot interactions through interpersonal manual tasks, revealing insights on performance differences and adaptation in human behavior.

Learning Bipedal Motor Skills: Challenges and Assistance

Explores challenges in humanoid reinforcement learning and the use of assistive forces in enhancing robot locomotion.

Biological Intelligence: Motor Learning and Neuromodulation

Explores the relationship between biological intelligence, motor learning, and the role of neuromodulation in adaptive behavior.

Robot Learning and Control

Covers learning and adaptive control for robots, focusing on real-time reactivity and path planning using dynamical systems.

Learning and Adaptive Control for Robots: Overview and Path Planning