THINK Robots

Retailers rely on Kiva Systems’ warehouse robots to deliver order-fulfillment services, but current systems are frequently interrupted and require physical barriers to ensure compliance with safety regulations since Kiva does not currently rely on the obstacle detection system to contribute to the functional safety of its overall system. After evaluating operating scenarios and detection technologies, a solution comprised of a stereo vision system to detect static objects and a radio ranging system to identify humans in the vicinity was designed, built, and verified, with the aim of reducing undue downtime and allowing humans and robots to safely interact without physical restrictions

Structure from motion using omni-directional vision and certainty grids

This thesis describes a method to create local maps from an omni-directional vision system (ODVS) mounted on a mobile robot. Range finding is performed by a structure-from-motion method, which recovers the three-dimensional position of objects in the environment from omni-directional images. This leads to map-making, which is accomplished using certainty grids to fuse information from multiple readings into a two-dimensional world model. The system is demonstrated both on noise-free data from a custom-built simulator and on real data from an omni-directional vision system on-board a mobile robot. Finally, to account for the particular error characteristics of a real omni-directional vision sensor, a new sensor model for the certainty grid framework is also created and compared to the traditional sonar sensor model

Mobile Robots Navigation

Mobile robots navigation includes different interrelated activities: (i) perception, as obtaining and interpreting sensory information; (ii) exploration, as the strategy that guides the robot to select the next direction to go; (iii) mapping, involving the construction of a spatial representation by using the sensory information perceived; (iv) localization, as the strategy to estimate the robot position within the spatial map; (v) path planning, as the strategy to find a path towards a goal location being optimal or not; and (vi) path execution, where motor actions are determined and adapted to environmental changes. The book addresses those activities by integrating results from the research work of several authors all over the world. Research cases are documented in 32 chapters organized within 7 categories next described

Night vision obstacle detection and avoidance based on Bio-Inspired Vision Sensors

Moving towards autonomy, unmanned vehicles rely heavily on state-of-the-art collision avoidance systems (CAS). However, the detection of obstacles especially during night-time is still a challenging task since the lighting conditions are not sufficient for traditional cameras to function properly. Therefore, we exploit the powerful attributes of event-based cameras to perform obstacle detection in low lighting conditions. Event cameras trigger events asynchronously at high output temporal rate with high dynamic range of up to 120 $dB$. The algorithm filters background activity noise and extracts objects using robust Hough transform technique. The depth of each detected object is computed by triangulating 2D features extracted utilising LC-Harris. Finally, asynchronous adaptive collision avoidance (AACA) algorithm is applied for effective avoidance. Qualitative evaluation is compared using event-camera and traditional camera.Comment: Accepted to IEEE SENSORS 202