Safe Motion Planning for Human-Robot Interaction: Design and Experiments [chapter]

Dana Kulic, Elizabeth Croft
2006 Mobile Robots: towards New Applications  
In industrial applications, the safety of human-robot interaction is effected by isolating the robot from the human (Gaskill and Went, 1996; Corke, 1999; RIA/ANSI, 1999) . In effect there is no interaction. As robots move from isolated industrial environments to interactive environments, this approach is no longer tenable (Corke, 1999) . Three main approaches can be used to mitigate the risk during human-robot interaction: (i) redesign the system to eliminate the hazard, (ii) control the hazard
more » ... through electronic or physical safeguards, and, (iii) warn the operator/user, either during operation or by training (RIA/ANSI, 1999). While the warn/train option has been used in industry, it had not been deemed effective in that setting (RIA/ANSI, 1999), and is even less suitable for robot interaction with untrained users. Examples of redesign include using a whole-body robot visco-elastic covering, and the use of spherical and compliant joints (Yamada, Hirawawa et al., 1997; Yamada, Yamamoto et al., 1999) . In unstructured environments, mechanical design alone is not adequate to ensure safe and human friendly interaction. Additional safety measures, utilizing system control and planning, are necessary. Several approaches have been proposed for ensuring safety through control. They focus on either slowing down or stopping when a hazardous situation is identified (Bearveldt, 1993; Yamada, Hirawawa et al., 1997; Zurada, Wright et al., 2001) , moving to evade contact (Traver, del Pobil et al., 2000) , or trying to minimize the impact force if contact occurs (Lew, Jou et al., 2000) . A key problem for all of these control methods is to identify when safety is threatened. One approach is to use tactile sensors and force/torque sensors to identify a hazard when unplanned contact occurs (Yamada, Hirawawa et al., 1997) . Recently, Ikuta et al. (Ikuta and Nokata, 2003) developed a danger evaluation method using the potential impact force as an evaluation measure. In their work, the danger index is defined as a product of factors which affect the potential impact force between the robot and the human, such as relative distance, relative velocity, robot inertia and robot stiffness. Motion planning and the a priori identification of potentially hazardous situations as a means of reducing potential robot-safety hazards has received less attention than control-based (reactive) techniques. However, safe planning is important for any interaction that involves motion in a human environment, especially those that may contain additional obstacles. Application examples include service scenarios such as a dish clearing robot (Bearveldt, 1993) , services for the disabled, such as approaching the human for a feeding task (Kawamura, Bagchi et al., 1995; Guglielmelli, Dario et al., 1996) , and pick and place tasks for picking up and delivering common objects (Bischoff and Graefe, 2004) . Including safety criteria at the planning stage can place the robot in a better position to respond to unanticipated safety events. Planning is thus used to improve the control outcome, similar to using smooth trajectory design to improve tracking (Erkorkmaz and Altintas, 2001; Macfarlane and Croft, 2003) . Several authors consider an a priori evaluation of the workspace to determine motion parameters within the various zones of the workspace (Bearveldt, 1993; Yamada, Hirawawa et al., 1997) . Blanco et al. (Blanco, Balaguer et al., 2002) use distance measures from a laser scanner to generate a Voronoi diagram of the workspace of a mobile manipulator performing co-operative load carrying with a human. Since the Voronoi diagram maximizes distance from obstacles, paths generated along the Voronoi diagram present the safest course in terms of collision potential. Khatib (Khatib, 1986) developed the potential field approach. In this method, the environment is described by an attractive (goal) potential field, which acts on the end effector, and a repulsive (obstacle) potential field, which acts on the entire robot body. The potential field is specified in the
doi:10.5772/4689 fatcat:r3c4fph76fcfney2thcntqd37m