Grasping and Control Issues in Adaptive End Effectors

Research into robotic grasping and manipulation has led to the development of a large number of tendon based end effectors. Many are, however, developed as a research tool, which are limited in application to the laboratory environment. The main reason being that the designs requiring a large number of actuators to be controlled. Due to the space and safety requirements, very few have been developed and commissioned for industrial applications. This paper presents design of a rigid link finger operated by a minimum number of actuators, which may be suitable for a number of adaptive end effectors. The adaptive nature built into the end effector (due to limited number of actuators) presents considerable problems in grasping and control. The paper discusses the issues associated with such designs. The research can be applicable to any adaptive end effectors that are controlled by limited number of actuators and evaluates their suitability in industrial environments

APPLE: Adaptive Planner Parameter Learning From Evaluative Feedback

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Exact Robot Navigation Using Power Diagrams

We reconsider the problem of reactive navigation in sphere worlds, i.e., the construction of a vector field over a compact, convex Euclidean subset punctured by Euclidean disks, whose flow brings a Euclidean disk robot from all but a zero measure set of initial conditions to a designated point destination, with the guarantee of no collisions along the way. We use power diagrams, generalized Voronoi diagrams with additive weights, to identify the robot’s collision free convex neighborhood, and to generate the value of our proposed candidate solution vector field at any free configuration via evaluation of an associated convex optimization problem. We prove that this scheme generates a continuous flow with the specified properties. We also propose its practical extension to the nonholonomically constrained kinematics of the standard differential drive vehicle.For more information: Kod*la

Adaptive Path Planning for Depth Constrained Bathymetric Mapping with an Autonomous Surface Vessel

This paper describes the design, implementation and testing of a suite of algorithms to enable depth constrained autonomous bathymetric (underwater topography) mapping by an Autonomous Surface Vessel (ASV). Given a target depth and a bounding polygon, the ASV will find and follow the intersection of the bounding polygon and the depth contour as modeled online with a Gaussian Process (GP). This intersection, once mapped, will then be used as a boundary within which a path will be planned for coverage to build a map of the Bathymetry. Methods for sequential updates to GP's are described allowing online fitting, prediction and hyper-parameter optimisation on a small embedded PC. New algorithms are introduced for the partitioning of convex polygons to allow efficient path planning for coverage. These algorithms are tested both in simulation and in the field with a small twin hull differential thrust vessel built for the task.Comment: 21 pages, 9 Figures, 1 Table. Submitted to The Journal of Field Robotic

Systematizing Gibsonian affordances in robotics: an empirical, generative approach derived from case studies in legged locomotion

A Gibsonian theory of affordances commits to direct perception and the mutuality of the agent-environment system. We argue that there already exists a research program in robotics which incorporates Gibsonian affordances. Controllers under this research program use information perceived directly from the environment with little or no further processing, and implicitly respect the indivisibility of the agentenvironment system. Research investigating the relationships between environmental and robot properties can be used to design reactive controllers that provably allow robots to take advantage of these affordances. We lay out key features of our empirical, generative Gibsonian approach and both show how it illuminates existing practice and suggest that it could be adopted to facilitate the systematic development of autonomous robots. We limit the scope of projects discussed here to legged robot systems but expect that applications can be found in other fields of robotics research. This paper was presented at the 2nd International Workshop on Computational Models of Affordances at ICRA 2019. For more information, see: Kod*la