Safe and Adaptive 3-D Locomotion via Constrained Task-Space Imitation Learning

Bipedal locomotion has been widely studied in recent years, where passive safety (i.e., a biped rapidly brakes without falling) is deemed to be a pivotal problem. To realize safe 3-D walking, existing works resort to nonlinear optimization techniques based on simplified dynamics models, requiring hand-tuned reference trajectories. In this...

Safer reinforcement learning for robotics

Reinforcement learning is an active research area in the fields of artificial intelligence and machine learning, with applications in control. The most important feature of reinforcement learning is its ability to learn without prior knowledge about the system. However, in the real world, reinforcement learning actions may lead to serious damage...

Combining multi-level real-time iterations of Nonlinear Model Predictive Control to realize squatting motions on Leo

Today’s humanoid robots are complex mechanical systems with many degrees of freedom that are built to achieve locomotion skills comparable to humans. In order to synthesize whole-body motions, real-tme capable direct methods of optimal control are a subject of contemporary research. To this end, Nonlinear Model Predictive Control is the method...

Affective Body Language of Humanoid Robots: Perception and Effects in Human Robot Interaction

Web API Fragility: How Robust is Your Mobile Application?

Web APIs provide a systematic and extensible approach for application-to-application interaction. A large number of mobile applications makes use of web APIs to integrate services into apps. Each Web API's evolution pace is determined by their respective developer and mobile application developers are forced to accompany the API providers in...

Active Vision for Humanoid Robots

Human perception is an active process. By altering its viewpoint rather than passively observing surroundings and by operating on sequences of images rather than on a single frame, the human visual system has the ability to explore the most relevant information based on knowledge, therefore when growing up a human is able to develop cognitive...

Unveiling exception handling bug hazards in Android based on GitHub and Google code issues

This paper reports on a study mining the exception stack traces included in 159,048 issues reported on Android projects hosted in GitHub (482 projects) and Google Code (157 projects). The goal of this study is to investigate whether stack trace information can reveal bug hazards related to exception handling code that may lead to a decrease...

A NAO robot playing tic-tac-toe: Comparing alternative methods for Inverse Kinematics

In this paper, two alternative methods to the Inverse Kinematics problem are compared to traditional methods regarding computation time, accuracy, and convergence rate. The test domain is the arm of the NAO humanoid robot. The results show that FABRIK, a heuristic iterative approximation algorithm outperforms the two traditional methods, which...

Fall detection in walking robots by multi-way principal component analysis

Large disturbances can cause a biped to fall. If an upcoming fall can be detected, damage can be minimized or the fall can be prevented. We introduce the multi-way principal component analysis (MPCA) method for the detection of upcoming falls. We study the detection capability of the MPCA method in a simulation study with the simplest walking...