Reactive direction control for a mobile robot: A locust-like control of escape direction emerges when a bilateral pair of model locust visual neurons are integrated

Locusts possess a bilateral pair of uniquely identifiable visual neurons that respond vigorously to the image of an approaching object. These neurons are called the lobula giant movement detectors (LGMDs). The locust LGMDs have been extensively studied and this has lead to the development of an LGMD model for use as an artificial collision detector in robotic applications. To date, robots have been equipped with only a single, central artificial LGMD sensor, and this triggers a non-directional stop or rotation when a potentially colliding object is detected. Clearly, for a robot to behave autonomously, it must react differently to stimuli approaching from different directions. In this study, we implement a bilateral pair of LGMD models in Khepera robots equipped with normal and panoramic cameras. We integrate the responses of these LGMD models using methodologies inspired by research on escape direction control in cockroaches. Using ‘randomised winner-take-all’ or ‘steering wheel’ algorithms for LGMD model integration, the khepera robots could escape an approaching threat in real time and with a similar distribution of escape directions as real locusts. We also found that by optimising these algorithms, we could use them to integrate the left and right DCMD responses of real jumping locusts offline and reproduce the actual escape directions that the locusts took in a particular trial. Our results significantly advance the development of an artificial collision detection and evasion system based on the locust LGMD by allowing it reactive control over robot behaviour. The success of this approach may also indicate some important areas to be pursued in future biological research

Overcoming barriers and increasing independence: service robots for elderly and disabled people

This paper discusses the potential for service robots to overcome barriers and increase independence of elderly and disabled people. It includes a brief overview of the existing uses of service robots by disabled and elderly people and advances in technology which will make new uses possible and provides suggestions for some of these new applications. The paper also considers the design and other conditions to be met for user acceptance. It also discusses the complementarity of assistive service robots and personal assistance and considers the types of applications and users for which service robots are and are not suitable

Material perception and action : The role of material properties in object handling

This dissertation is about visual perception of material properties and their role in preparation for object handling. Usually before an object is touched or picked-up we estimate its size and shape based on visual features to plan the grip size of our hand. After we have touched the object, the grip size is adjusted according to the provided haptic feedback and the object is handled safely. Similarly, we anticipate the required grip force to handle the object without slippage, based on its visual features and prior experience with similar objects. Previous studies on object handling have mostly examined object characteristics that are typical for object recognition, e.g., size, shape, weight, but in the recent years there has been a growing interest in object characteristics that are more typical to the type of material the object is made from. That said, in a series of studies we investigated the role of perceived material properties in decision-making and object handling, in which both digitally rendered materials and real objects made of different types of materials were presented to human subjects and a humanoid robot. Paper I is a reach-to-grasp study where human subjects were examined using motion capture technology. In this study, participants grasped and lifted paper cups that varied in appearance (i.e., matte vs. glossy) and weight. Here we were interested in both the temporal and spatial components of prehension to examine the role of material properties in grip preparation, and how visual features contribute to inferred hardness before haptic feedback has become available. We found the temporal and spatial components were not exclusively governed by the expected weight of the paper cups, instead glossiness and expected hardness has a significant role as well. In paper II, which is a follow-up on Paper I, we investigated the grip force component of prehension using the same experimental stimuli as used in paper I. In a similar experimental set up, using force sensors we examined the early grip force magnitudes applied by human subjects when grasping and lifting the same paper cups as used in Paper I. Here we found that early grip force scaling was not only guided by the object weight, but the visual characteristics of the material (i.e., matte vs. glossy) had a role as well. Moreover, the results suggest that grip force scaling during the initial object lifts is guided by expected hardness that is to some extend based on visual material properties. Paper III is a visual judgment task where psychophysical measurements were used to examine how the material properties, roughness and glossiness, influence perceived bounce height and consequently perceived hardness. In a paired-comparison task, human subjects observed a bouncing ball bounce on various surface planes and judged their bounce height. Here we investigated, what combination of surface properties, i.e., roughness or glossiness, makes a surface plane to be perceived bounceable. The results demonstrate that surface planes with rough properties are believed to afford higher bounce heights for the bouncing ball, compared to surface planes with smooth properties. Interestingly, adding shiny properties to the rough and smooth surface planes, reduced the judged difference, as if surface planes with gloss are believed to afford higher bounce heights irrespective of how smooth or rough the surface plane is beneath. This suggests that perceived bounce height involves not only the physical elements of the bounce height, but also the visual characteristics of the material properties of the surface planes the ball bounces on. In paper IV we investigated the development of material knowledge using a robotic system. A humanoid robot explored real objects made of different types of materials, using both camera and haptic systems. The objects varied in visual appearances (e.g., texture, color, shape, size), weight, and hardness, and in two experiments, the robot picked up and placed the experimental objects several times using its arm. Here we used the haptic signals from the servos controlling the arm and the shoulder of the robot, to obtain measurements of the weight and hardness of the objects, and the camera system to collect data on the visual features of the objects. After the robot had repeatedly explored the objects, an associative learning model was created based on the training data to demonstrate how the robotic system could produce multi-modal mapping between the visual and haptic features of the objects. In sum, in this thesis we show that visual material properties and prior knowledge of how materials look like and behave like has a significant role in action planning

Multi-Agent Task Allocation for Robot Soccer

This is the published version. Copyright De GruyterThis paper models and analyzes task allocation methodologies for multiagent systems. The evaluation process was implemented as a collection of simulated soccer matches. A soccer-simulation software package was used as the test-bed as it provided the necessary features for implementing and testing the methodologies. The methodologies were tested through competitions with a number of available soccer strategies. Soccer game scores, communication, robustness, fault-tolerance, and replanning capabilities were the parameters used as the evaluation criteria for the mul1i-agent systems

Development and evaluation of a haptic framework supporting telerehabilitation robotics and group interaction

Telerehabilitation robotics has grown remarkably in the past few years. It can provide intensive training to people with special needs remotely while facilitating therapists to observe the whole process. Telerehabilitation robotics is a promising solution supporting routine care which can help to transform face-to-face and one-on-one treatment sessions that require not only intensive human resource but are also restricted to some specialised care centres to treatments that are technology-based (less human involvement) and easy to access remotely from anywhere. However, there are some limitations such as network latency, jitter, and delay of the internet that can affect negatively user experience and quality of the treatment session. Moreover, the lack of social interaction since all treatments are performed over the internet can reduce motivation of the patients. As a result, these limitations are making it very difficult to deliver an efficient recovery plan. This thesis developed and evaluated a new framework designed to facilitate telerehabilitation robotics. The framework integrates multiple cutting-edge technologies to generate playful activities that involve group interaction with binaural audio, visual, and haptic feedback with robot interaction in a variety of environments. The research questions asked were: 1) Can activity mediated by technology motivate and influence the behaviour of users, so that they engage in the activity and sustain a good level of motivation? 2) Will working as a group enhance users’ motivation and interaction? 3) Can we transfer real life activity involving group interaction to virtual domain and deliver it reliably via the internet? There were three goals in this work: first was to compare people’s behaviours and motivations while doing the task in a group and on their own; second was to determine whether group interaction in virtual and reala environments was different from each other in terms of performance, engagement and strategy to complete the task; finally was to test out the effectiveness of the framework based on the benchmarks generated from socially assistive robotics literature. Three studies have been conducted to achieve the first goal, two with healthy participants and one with seven autistic children. The first study observed how people react in a challenging group task while the other two studies compared group and individual interactions. The results obtained from these studies showed that the group interactions were more enjoyable than individual interactions and most likely had more positive effects in terms of user behaviours. This suggests that the group interaction approach has the potential to motivate individuals to make more movements and be more active and could be applied in the future for more serious therapy. Another study has been conducted to measure group interaction’s performance in virtual and real environments and pointed out which aspect influences users’ strategy for dealing with the task. The results from this study helped to form a better understanding to predict a user’s behaviour in a collaborative task. A simulation has been run to compare the results generated from the predictor and the real data. It has shown that, with an appropriate training method, the predictor can perform very well. This thesis has demonstrated the feasibility of group interaction via the internet using robotic technology which could be beneficial for people who require social interaction (e.g. stroke patients and autistic children) in their treatments without regular visits to the clinical centres

Proceedings of the 4th Baltic Mechatronics Symposium - Tallinn April 25, 2019

The Baltic Mechatronics Symposium is annual symposium with the objective to provide a forum for young scientists from Baltic countries to exchange knowledge, experience, results and information in large variety of fields in mechatronics. The symposium was organized in co-operation with Taltech and Aalto University. The venue of the symposium was Nordic Hotel Forum Tallinn.The symposium was organized parallel to the 12th International DAAAM Baltic Conference and 27th International Baltic Conference BALTMATTRIB 2019. The selected papers are published in Proceedings of Estonian Academy of Sciences indexed in ISI Web of Science. The content of the proceedings: 1. Continuous wet spinning of cellulose nanofibrils 2. Development of motor efficiency test setup for direct driven hydraulic actuator 3. Development of pressure former for continuous nanopaper manufacturing 4. Device for tree volume measurements 5. Effect of external load on rotor vibration 6. Granular jamming based gripper for heavy objects 7. Integrated car camera system for monitoring inner cabin and outer traffic 8. Inverted pendulum controlled with CNC control system 9. Multi-material mixer and extruder for 3D printing 10. Object detection and trajectory planning using a LIDAR for an automated overhead cran

Ground Robotic Hand Applications for the Space Program study (GRASP)

This document reports on a NASA-STDP effort to address research interests of the NASA Kennedy Space Center (KSC) through a study entitled, Ground Robotic-Hand Applications for the Space Program (GRASP). The primary objective of the GRASP study was to identify beneficial applications of specialized end-effectors and robotic hand devices for automating any ground operations which are performed at the Kennedy Space Center. Thus, operations for expendable vehicles, the Space Shuttle and its components, and all payloads were included in the study. Typical benefits of automating operations, or augmenting human operators performing physical tasks, include: reduced costs; enhanced safety and reliability; and reduced processing turnaround time