Exploration of Surfaces for Robot Mobility

This paper presents an overview of ongoing research in surface exploration at the GRASP Lab. The objective of the work presented here is to design a system that will explore an environment that is unknown and unconstrained and will enable a robot to adapt to varying surroundings. We are investigating the necessary components/modules that must be embedded into a robot for it to have exploratory capabilities. We have designed and are implementing exploratory procedures (ep\u27s) to recover the mechanical properties from a surface given minimal a priori information so that a robot or a vehicle can decide whether to and how to move on this surface. The laboratory setup involves a compliant wrist with six degrees of freedom, mounted on a robot arm, and a laser range finder, mounted on another robot arm, as the primary sensors to detect the response of surfaces with varying mechanical properties

Active Exploration of Surfaces for Legged Locomotion of Robots

This paper presents some results of an ongoing research project in the GRASP Lab in the area of active exploration and perception for the legged locomotion of robots. We propose an active perceptual scheme that is based on the ability of the robot to extract material properties from a surface during locomotion. This ability is provided to the robotic system through a compliant sensing device which is used to monitor the response of the surface when exploratory procedures are executed during the stepping and walking motions of the leg. Such a system will actively perceive changes in the surfaces properties and prevent the robot from slipping, falling, or sinking during locomotion. The paper describes the proposed perceptual scheme, the system set-up, and the implementation of the exploratory procedures

Robotic Exploration of Surfaces to Measure Mechanical Properties

This paper presents an overview of ongoing research on surface exploration at the GRASP Lab. We are investigating the necessary components and modules that must be embedded into a robot for it to have the exploratory capabilities required to recover mechanical properties from a surface, given minimal a priori information. Eventually, this information will be used to enable a robot to stand and walk stably on a surface that is unknown and unconstrained. A robot in the agricultural environment will specially benefit from such capabilities since it will need to step and walk on soils with variable properties. The paper proposes a framework for the recovery of the attributes of interest, and describes the laboratory setup designed to test the framework. The design and implementation of exploratory procedures (ep\u27s) to recover penetrability, material hardness and surface roughness by exploring the surface is also described

Visual Observation of a Moving Agent

We address the problem of observing a moving agent. In particular, we propose a system for observing a manipulation process, where a robot hand manipulates an object. A discrete event dynamic systems (DEDS) frame work is developed for the hand/object interaction over time and a stabilizing observer is constructed. Low-level modules are developed for recognizing the events that causes state transitions within the dynamic manipulation system. The work examines closely the possibilities for errors, mistakes and uncertainties in the manipulation system, observer construction process and event identification mechanisms. The system utilizes different tracking techniques in order to observe and recognize the task in an active, adaptive and goal-directed manner

Exploration of Unknown Mechanical Assemblies Through Manipulation

If robots must function in unstructured environments, they must also possess the ability to acquire information and construct appropriate models of the unknown environment. This paper addresses the automatic generation of kinematic models of unknown objects with moveable parts in the environment. If the relative motion between moving parts must be observed and characterized, vision alone cannot suffice. An approach in which manipulation is used with vision for sensing is better suited to the task of determining kinematic properties. In this paper, algorithms for constructing models of unknown mechanical assemblies and characterizing the relative motion are developed. Results of a simulation are described to demonstrate the role of manipulation in such an endeavor

A Hand-Eye-Arm Coordinated System

In this paper we present the description and experiments with a tightly coupled Hand-Eye-Arm manipulatory system. We explain the philosophy and the motivation for building a tightly coupled system that actually consists of very autonomous modules that communicate with each other via a central coordinator. We describe each of the modules in the system and their interactions with each other. We highlight the need for sensory driven manipulation, and explain how the above system, where the hand is equipped with multiple tactile sensors, is capable of both manipulating unknown objects, but also detecting and complying in the case of collisions. We explain the partition of the control of the system into various closed loops, representing coordination both at the level of gross manipulator motions as well as fine motions. We describe the various modes that the system can work in, as well as some of the experiments that are being currently performed using this system