19 accepted papers
We present a new causal transformer system consisting of Spatial-Attention Tokenization (SAT) with MultiResolution Causal Temporal Mixing (MRCTM) to perform online skeleton-based action recognition during human–robot interaction. The novel architecture uses Spatial-Attention Tokenization (SAT) to ge…
This paper presents Spiking-Refined 3D Object Detection through YOLO–SNN Fusion, a real-time pipeline that leverages both convolutional and spiking neural representations for enhanced scene perception. Our system integrates YOLOv11 for robust 2D detection, Depth Anything v2 for monocular depth infer…
Telemanipulation enables humans to perform tasks in dangerous environments without exposing them to any risk. The COVID-19 pandemic sadly showed, that these environments can also include the treatment and interaction with infected patients. Since human-robot interactions demand for low interaction f…
Ensuring safe interaction between humans and robots is an important challenge in robotics. In recent years, researchers have developed many different soft robots. One possibility to reach this goal is to integrate mechanical springs into their joints. The forthcoming generation of soft robots will b…
Gaze estimation provides insight into a person's intent and engagement level, which is helpful in collaborative human-robot applications. With significant advancements in deep learning architectures, appearance-based gaze estimation has gained much attention. Appearance-based methods have shown sign…
Sampling-based motion planning algorithms have been continuously developed for more than two decades. Apart from mobile robots, they are also widely used in manipulator motion planning. Hence, these methods play a key role in collaborative and shared workspaces. Despite numerous improvements, their…
In this paper a novel full state feedback approach for control of compliant actuated robot with nonlinear spring characteristics is presented. A multi-DOF elastic robot arm is a multi-input multi-output (MIMO) under-actuated system. By the new novel controller, which is based on motor coordinate tra…
A robot must comply with very restrictive safety standards in close human-robot collaboration applications. These standards limit the robot's performance because of speed reductions to avoid potentially large forces exerted on humans during collisions. On-robot capacitive proximity sensors (CPS) can…
In recent years, haptic telemanipulation has been introduced to control robots remotely with an input device that generates force feedback. Compliant control strategies are needed to ensure safe interaction between humans and robots. Accurate and precise manipulation requires a stiff setup of the im…
During the co-presence of human workers and robots, measures are required to avoid injuries from undesired contacts. Capacitive Proximity Sensors (CPSs) offer a cost-effective solution to cover the entire robot manipulator with fast close-range perception for HRC tasks, closing the perception gap be…
Natural and human-like arm motions are promising features to facilitate social understanding of humanoid robots. To this end, we integrate biophysical characteristics of human arm-motions into sampling-based motion planning. We show the generality of our method by evaluating it with multiple manipul…
We present a system which improves the safety and accuracy of impedance controlled robotic manipulators with proximity perception. Proximity servoed manipulators, which use proximity sensors attached to the robot’s outer shell, have recently demonstrated robust collision avoidance abilities. Neverth…
Collision avoidance is a key technology towards safe human-robot interaction, especially on-line and fastreacting motions are required. Skins with proximity sensors mounted on the robot's outer shell provide an interesting approach to occlusion-free and low-latency perception. However, collision avo…
The ability of detecting materials plays an important role in robotic applications. The robot can incorporate the information from contactless material detection and adapt its behavior in how it grasps an object or how it walks on specific surfaces. In this, paper we apply machine learning on impeda…
In this paper, we present a serial kinematic robot manipulator equipped with multimodal proximity sensing modules not only on the TCP but distributed on the robot's surface. The combination of close distance proximity information from capacitive and time-of-flight (ToF) measurements allows the robot…
We present a new general framework for disassembly sequence planning. This framework is versatile allowing different types of search schemes (exhaustive vs. preemptive), various part separation techniques, and the ability to group parts, or not, into subassemblies to improve the solution efficiency…
In this paper, we present a method for contactless material detection with capacitive proximity sensing skins. Our new approach extends the current state-of-the-art proximity and distance sensing methods and measures the characteristic impedance spectrum of an object to obtain material properties. B…
In classical robot-camera calibration, a 6D transformation between the camera frame and the local frame of a robot is estimated by first observing a known calibration object from a number of different view points and then finding transformation parameters that minimize the reprojection error. The di…
This paper presents a new approach for error robust assembly sequence planning which uses haptic rendering models (HRMs) for the representation of assemblies. Our assembly planning system uses HRMs for collision test along mating vectors, which are generated by stereographic projection. The planner…