Jörg Conradt

IROS Conference 2020 Conference Paper

A Miniaturised Neuromorphic Tactile Sensor integrated with an Anthropomorphic Robot Hand

• Benjamin Ward-Cherrier
• Jörg Conradt
• Manuel G. Catalano
• Matteo Bianchi 0002
• Nathan F. Lepora

Restoring tactile sensation is essential to enable in-hand manipulation and the smooth, natural control of upper-limb prosthetic devices. Here we present a platform to contribute to that long-term vision, combining an anthropomorphic robot hand (QB SoftHand) with a neuromorphic optical tactile sensor (neuroTac). Neuromorphic sensors aim to produce efficient, spike-based representations of information for bio-inspired processing. The development of this 5-fingered, sensorized hardware platform is validated with a customized mount allowing manual control of the hand. The platform is demonstrated to succesfully identify 4 objects from the YCB object set, and accurately discriminate between 4 directions of shear during stable grasps. This platform could lead to wide-ranging developments in the areas of haptics, prosthetics and telerobotics.

ICRA Conference 2014 Conference Paper

Event-based 3D SLAM with a depth-augmented dynamic vision sensor

• David Weikersdorfer
• David B. Adrian
• Daniel Cremers
• Jörg Conradt

We present the D-eDVS- a combined event-based 3D sensor — and a novel event-based full-3D simultaneous localization and mapping algorithm which works exclusively with the sparse stream of visual data provided by the D-eDVS. The D-eDVS is a combination of the established PrimeSense RGB-D sensor and a biologically inspired embedded dynamic vision sensor. Dynamic vision sensors only react to dynamic contrast changes and output data in form of a sparse stream of events which represent individual pixel locations. We demonstrate how an event-based dynamic vision sensor can be fused with a classic frame-based RGB-D sensor to produce a sparse stream of depth-augmented 3D points. The advantages of a sparse, event-based stream are a much smaller amount of generated data, thus more efficient resource usage, and a continuous representation of motion allowing lag-free tracking. Our event-based SLAM algorithm is highly efficient and runs 20 times faster than realtime, provides localization updates at several hundred Hertz, and produces excellent results. We compare our method against ground truth from an external tracking system and two state-of-the-art algorithms on a new dataset which we release in combination with this paper.

ICRA Conference 2014 Conference Paper

Event-based neural computing on an autonomous mobile platform

• Francesco Galluppi
• Christian Denk
• Matthias C. Meiner
• Terrence C. Stewart
• Luis A. Plana
• Chris Eliasmith
• Steve B. Furber
• Jörg Conradt

Living organisms are capable of autonomously adapting to dynamically changing environments by receiving inputs from highly specialized sensory organs and elaborating them on the same parallel, power-efficient neural substrate. In this paper we present a prototype for a comprehensive integrated platform that allows replicating principles of neural information processing in real-time. Our system consists of (a) an autonomous mobile robotic platform, (b) on-board actuators and multiple (neuromorphic) sensors, and (c) the SpiNNaker computing system, a configurable neural architecture for exploration of parallel, brain-inspired models. The simulation of neurally inspired perception and reasoning algorithms is performed in real-time by distributed, low-power, low-latency event-driven computing nodes, which can be flexibly configured using C or specialized neural languages such as PyNN and Nengo. We conclude by demonstrating the platform in two experimental scenarios, exhibiting real-world closed loop behavior consisting of environmental perception, reasoning and execution of adequate motor actions.

IROS Conference 2002 Conference Paper

Ada: constructing a synthetic organism

• Kynan Eng
• Andreas Bäbler
• Ulysses Bernardet
• Mark Blanchard
• Adam Briska
• Jörg Conradt
• Márcio O. Costa
• Tobi Delbruck

Despite immense progress in neuroscience, we remain restricted in our ability to construct autonomous behaving robots that match the competence of even simple animals. The barriers to the realisation of this goal include: the lack of knowledge of system integration issues, engineering limitations and organisational constraints common to many research laboratories. In this paper we describe our approach to addressing these issues by constructing an artificial organism within the framework of the Ada project - a large-scale public exhibit for the Swiss Expo. 02 national exhibition.

IROS Conference 2001 Conference Paper

Overt visual attention for a humanoid robot

• Sethu Vijayakumar
• Jörg Conradt
• Tomohiro Shibata
• Stefan Schaal

The goal of our research is to investigate the interplay between oculomotor control, visual processing, and limb control in humans and primates by exploring the computational issues of these processes with a biologically inspired artificial oculomotor system on an anthropomorphic robot. In this paper, we investigate the computational mechanisms for visual attention in such a system. Stimuli in the environment excite a dynamical neural network that implements a saliency map, i. e. , a winner-take-all competition between stimuli while simultaneously smoothing out noise and suppressing irrelevant inputs. In real-time, this system computes new targets for the shift of gaze, executed by the head-eye system of the robot. The redundant degrees-of-freedom of the head-eye system are resolved through a learned inverse kinematics with optimization criterion. We also address important issues how to ensure that the coordinate system of the saliency map remains correct after movement of the robot. The presented attention system is built on principled modules and generally applicable for any sensory modality.

ICML Conference 2000 Conference Paper

On-line Learning for Humanoid Robot Systems

• Jörg Conradt
• Gaurav Tevatia
• Sethu Vijayakumar
• Stefan Schaal