Related papers: Unsupervised Neural Motion Retargeting for Humanoi…
Human teams are able to easily perform collaborative manipulation tasks. However, for a robot and human to simultaneously manipulate an extended object is a difficult task using existing methods from the literature. Our approach in this…
Predicting and understanding human motion dynamics has many applications, such as motion synthesis, augmented reality, security, and autonomous vehicles. Due to the recent success of generative adversarial networks (GAN), there has been…
When humans control drones, cars, and robots, we often have some preconceived notion of how our inputs should make the system behave. Existing approaches to teleoperation typically assume a one-size-fits-all approach, where the designers…
In this paper, we present a multimodal mobile teleoperation system that consists of a novel vision-based hand pose regression network (Transteleop) and an IMU-based arm tracking method. Transteleop observes the human hand through a low-cost…
Scalable learning of humanoid robots is crucial for their deployment in real-world applications. While traditional approaches primarily rely on reinforcement learning or teleoperation to achieve whole-body control, they are often limited by…
This paper presents an object-aware whole-body bilateral teleoperation framework for wheeled humanoid loco-manipulation. This framework combines whole-body bilateral teleoperation with an online multi-stage object inertial parameter…
Humanoid robots rely on multi-contact planners to navigate a diverse set of environments, including those that are unstructured and highly constrained. To synthesize stable multi-contact plans within a reasonable time frame, most planners…
Humans directly completing tasks in dangerous or hazardous conditions is not always possible where these tasks are increasingly be performed remotely by teleoperated robots. However, teleoperation is difficult since the operator feels a…
Tool use is essential for enabling robots to perform complex real-world tasks, but learning such skills requires extensive datasets. While teleoperation is widely used, it is slow, delay-sensitive, and poorly suited for dynamic tasks. In…
Teleoperation is a widely adopted strategy to control robotic manipulators executing complex tasks that require highly dexterous movements and critical high-level intelligence. Classical teleoperation schemes are based on either joystick…
Ergonomic assessment of human posture plays a vital role in understanding work-related safety and health. Current posture estimation approaches face occlusion challenges in teleoperation and physical human-robot interaction. We investigate…
Teleoperation enables remote human support of automated vehicles in scenarios where the automation is not able to find an appropriate solution. Remote assistance concepts, where operators provide discrete inputs to aid specific automation…
Robot teleoperation gains great success in various situations, including chemical pollution rescue, disaster relief, and long-distance manipulation. In this article, we propose a virtual reality (VR) based robot teleoperation system to…
Most recent view-invariant action recognition and performance assessment approaches rely on a large amount of annotated 3D skeleton data to extract view-invariant features. However, acquiring 3D skeleton data can be cumbersome, if not…
This paper proposes an architecture for achieving telexistence and teleoperation of humanoid robots. The architecture combines several technological set-ups, methodologies, locomotion and manipulation algorithms in a novel manner, thus…
Teleoperation can transfer human perception and cognition to a slave robot to cope with some complex tasks, in which the agility and flexibility of the interface play an important role in mapping human intention to the robot. In this paper,…
3D human motion prediction, predicting future poses from a given sequence, is an issue of great significance and challenge in computer vision and machine intelligence, which can help machines in understanding human behaviors. Due to the…
Harnessing human movements to command an Unmanned Aerial Vehicle (UAV) holds the potential to revolutionize their deployment, rendering it more intuitive and user-centric. In this research, we introduce a novel methodology adept at…
This work presents a motion retargeting approach for legged robots, aimed at transferring the dynamic and agile movements to robots from source motions. In particular, we guide the imitation learning procedures by transferring motions from…
We build a system that enables any human to control a robot hand and arm, simply by demonstrating motions with their own hand. The robot observes the human operator via a single RGB camera and imitates their actions in real-time. Human…