Safe robotic grasping: Minimum impact-force grasp selection

Abstract

Abstract-This paper addresses the problem of selecting from a choice of possible grasps, so that impact forces will be minimised if a collision occurs while the robot is moving the grasped object along a post-grasp trajectory. Such considerations are important for safety in human-robot interaction, where even a certified "human-safe" (e.g. compliant) arm may become hazardous once it grasps and begins moving an object, which may have significant mass, sharp edges or other dangers. Additionally, minimising collision forces is critical to preserving longevity of robots which operate in uncertain and hazardous environments, e.g. robots deployed for nuclear decommissioning, where removing a damaged robot from a contaminated zone for repairs may be extremely difficult and costly. Also, unwanted collisions between a robot and critical infrastructure (e.g. pipework) in such high-consequence environments can be disastrous. In this paper we investigate how the safety of the post-grasp motion can be considered during the pre-grasp approach phase, so that the selected grasp is optimal in terms applying minimum impact forces if a collision occurs during a desired post-grasp manipulation. We build on the methods of augmented robot-object dynamics models and "effective mass" and propose a method for combining these concepts with modern grasp and trajectory planners, to enable the robot to achieve a grasp which maximises the safety of the postgrasp trajectory, by minimising potential collision forces. We demonstrate the effectiveness of our approach through several experiments with both simulated and real robots.

Design of a fuzzy safety margin derivation system for grip force control of robotic hand in precision grasp task

“…Fn m shown in Figure 2 is the normal force (Fn) value plus Sm (safety margin) applied by each finger when lifting event occurs. Fn m can be expressed as in equation (2).…”

“…For a robotic hand, grasping and manipulation is a complex task containing a movement plan in terms of kinematic and force control in both statics and dynamics. 2 The reason why this task is complex is due to the problems associated with the geometry, durability, hardness, and surface properties of the object to be gripped. The analytical modeling problems related to these issues are classified by Cutkosky 1 as follows: Geometry Kinematic Dynamic Constitutive relations.…”

Estimation and exploitation of objects ’ inertial parameters in robotic grasping and manipulation: A survey

“…The selection criterion is based on the object's inertial parameters. Image from [86]. (b) Again, the robot uses the inertial parameters to select a grasp that will minimise the required joint torque to execute a task.…”

Estimating An Object’s Inertial Parameters By Robotic Pushing: A Data-Driven Approach

“…This equation, anong with Eqs. (4) and (3) give the velocity of the object as a function of the pusher velocity:…”

“…Apart from visual info, recent research has shown that the inertial properties of an object, namely mass, centre of mass (CoM) and inertia tensor (which encodes the mass distribution), can make the grasping and manipulation process more efficient. Examples include minimum-disturbance grasp synthesis [1], as well as safe and minimum-effort manipulation planning [2] [3]. As a result, it is highly beneficial for an autonomous robot to be able to estimate the handled object's inertial parameters prior to grasping it, as this can lead to more efficient manipulation.…”